Unique neural signatures of childhood sexual abuse revisited

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Leehr , Linda M. Bonnekoh , View ORCID Profile Dominik Grotegerd , View ORCID Profile Nils Winter , Tim Hahn , View ORCID Profile Benjamin Straube , View ORCID Profile Hamidreza Jamalabadi , Andreas Jansen , Axel Krug , View ORCID Profile Udo Dannlowski , Igor Nenadić , View ORCID Profile Elvisha Dhamala , View ORCID Profile Tilo Kircher , Nina Alexander doi: https://doi.org/10.1101/2025.02.10.25322009 Katharina Brosch a Institute of Behavioral Science, Feinstein Institutes for Medical Research , Manhasset, NY, USA b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany c University Hospital Marburg, UKGM , Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Katharina Brosch For correspondence: kbrosch{at}northwell.edu Vincent Hammes b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Vincent Hammes Paula Usemann b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Paula Usemann Frederike Stein b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Frederike Stein Stephanie Zika b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Stephanie Zika Franziska Schrott b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Florian Thomas-Odenthal b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Florian Thomas-Odenthal Lea Teutenberg b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lea Teutenberg Susanne Meinert e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Susanne Meinert Katharina Thiel e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kira Flinkenflügel e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kira Flinkenflügel Navid Schürmeyer e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Janik Goltermann e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Janik Goltermann Elisabeth J. Leehr e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Linda M. Bonnekoh e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dominik Grotegerd e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Dominik Grotegerd Nils Winter e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nils Winter Tim Hahn e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Benjamin Straube b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Benjamin Straube Hamidreza Jamalabadi b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hamidreza Jamalabadi Andreas Jansen b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Axel Krug b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany f Department of Psychiatry and Psychotherapy, University Hospital Bonn , Bonn, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Udo Dannlowski e Institute for Translational Psychiatry, University of Münster, Albert-Schweitzer-Campus 1 , Building A9a, 48149 Münster, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Udo Dannlowski Igor Nenadić b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany c University Hospital Marburg, UKGM , Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elvisha Dhamala a Institute of Behavioral Science, Feinstein Institutes for Medical Research , Manhasset, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Elvisha Dhamala Tilo Kircher b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany c University Hospital Marburg, UKGM , Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Tilo Kircher Nina Alexander b Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg , Germany c University Hospital Marburg, UKGM , Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany d Center for Mind, Brain and Behavior (CMBB) , Hans-Meerwein-Str. 6, 35032 Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Childhood sexual abuse (CSA) constitutes a detrimental subtype of childhood maltreatment (CM) associated with high trauma load and adverse health outcomes. Previous studies indicate CSA-specific reductions in gray matter volume (GMV) and cortical thickness. It remains challenging to disentangle brain alterations associated with CSA from those related to trauma intensity or psychopathology. Here, we apply a novel approach, comparing individuals with CSA, non-sexual maltreatment, and a non-maltreated control group, to identify CSA-specific findings. Drawing from a cohort of n =2039 depressed and healthy men and women allowed us to match groups 1:1 for age, sex, depression diagnosis, and, for maltreated groups, trauma load. The Childhood Trauma Questionnaire was used to assess childhood maltreatment. Applying threshold-free cluster enhancement, we investigated GMV and cortical thickness in n =195 adults with CSA compared to non-sexually maltreated ( nCSA , n =195) and non-maltreated ( nCM , n =195) individuals. CSA showed larger GMV in the right cerebellum compared to nCSA but not compared to nCM . CSA displayed larger cortical thickness encompassing the bilateral superior frontal gyri, pre- and postcentral gyri, supramarginal gyri, superior parietal cortices, precunei, and insulae, compared to both nCSA and nCM . This is the largest study to investigate CSA-specific effects on brain morphometry, applying matched group comparisons. These findings highlight distinct neural signatures of CSA, characterized by preserved cortical thickness in regions also affected by major depression, and larger cerebellar GMV compared to non-sexual types of maltreatment. These results underscore the importance of distinguishing between types of childhood maltreatment and considering confounding factors when assessing their neurobiological impacts. Introduction Childhood maltreatment (CM) is associated with long-term alterations in brain structure ( 1 ). CM is considered a heterogeneous entity of multiple adverse experiences during childhood, encompassing sexual, physical, and emotional abuse, and physical and emotional neglect ( 2 ). These subtypes vary in degree of threat and deprivation ( 3 , 4 ). Threat constitutes harm to one’s bodily integrity, whereas deprivation constitutes the absence of adequate environmental stimulation ( 5 ). Childhood sexual abuse (CSA) is a particularly detrimental threat subtype of CM and associated with adverse and long-lasting mental and physical health outcomes ( 6 ). Worldwide, one in 5 women and one in 13 men report experiences of CSA ( 7 ). Survivors of CSA have an increased risk of developing several psychiatric disorders, such as major depressive disorder (MDD), anxiety disorder, post-traumatic stress disorder (PTSD), borderline personality disorder, schizophrenia, eating disorders, conversion disorder, and somatoform disorders ( 6 ). Adverse physical health outcomes of CSA include increased risk for fibromyalgia and obesity ( 6 , 8 – 10 ). While most CM research has focused on investigating the general adverse effects of all different subtypes combined, previous studies have also demonstrated differential effects of specific trauma subtypes on outcome domains such as structural and functional brain changes, inflammation, and emotion dynamics ( 4 , 11 – 14 ). Identifying such differential outcomes may inform targeted prevention and intervention strategies to optimally treat adverse outcomes of specific CM subtypes ( 15 ). Neuroimaging approaches have been central in CM research: during sensitive phases of brain development in childhood and adolescence, environmental influences can be particularly impactful ( 4 ). A recent meta-analysis summarizing 45 studies found consistent evidence of smaller cortical thickness and gray matter volume (GMV) in the median cingulate and paracingulate gyri, associated with general CM experiences. Further, smaller GMV in the supplementary motor area and smaller cortical thickness in the anterior cingulate/paracingulate gyri and left middle frontal gyrus were reported in individuals with CM ( 1 ). However, structural CM findings remain inconsistent across individual studies, which has been explained by factors such as heterogeneous cohort demographics, timing of CM, frequency of exposure, and specific subtype of CM ( 1 , 4 , 11 , 16 , 17 ). In CSA, MRI studies that included psychiatric patients and healthy controls reported unique morphometric signatures ( 18 ). Specifically, earlier studies identified brain morphometric alterations in CSA survivors compared to non-victimized controls in the hippocampus, the frontal cortex, the dorsal anterior cingulate cortex, and the corpus callosum ( 19 – 23 ). Importantly, the group differences in brain structure identified in studies comparing CSA to no CM may reflect neural correlates of general maltreatment exposure rather than specific effects of CSA ( 24 , 25 ). These neural differences could potentially be observed across different types of maltreatment. The few studies exploring the specificity of CSA by explicitly comparing the effects of different types of CM have yielded inconsistent results. Investigating cortical thickness, Heim et al. examined the differential effects of CM subtypes in a sample of adult women ( 26 ). Here, CSA was associated with cortical thinning in the genital representation field of the primary somatosensory cortex when controlling for other types of CM and depression using regression analysis ( 26 ). Tomoda et al. ( 27 ) demonstrated reduced GMV in the visual cortex of young women exposed to CSA compared to healthy controls without CSA exposure. Respective effects were found to be partly stable when excluding CSA individuals with psychopathology. Other studies further reported significantly smaller cortical thickness in the left rostral middle frontal gyrus, the bilateral fusiform gyri, and the right supramarginal gyrus and reduced GMV in the middle occipital gyrus in individuals exposed vs. not exposed to CSA ( 25 , 28 ). Concurrently, these effects were not observed for other types of CM. In patients with MDD, CSA and other types of CM were negatively correlated with entorhinal thickness and hippocampal volume ( 29 ). Previous literature on CSA-specific effects on brain morphology has generally relied on smaller sample sizes (with less than n =35 or unreported numbers of individuals exposed to CSA in individual studies) that may not generalize across different populations ( 26 , 27 ). Additional considerations impede the interpretability of CSA-specific effects in current research, which are 1) dose-dependent effects (i.e. confounding effects of higher trauma load) and 2) effects of psychopathology. First, some studies suggest that CSA is related to more negative health outcomes than other types of CM ( 30 ). However, this finding might not be a consequence of the specific exposure to CSA per se but could result from a generally higher trauma load observed in CSA survivors ( 30 ). Dose-dependent effects of CM have been reported before, and CM severity was associated with more severe psychopathological symptoms and increased cortical thinning ( 9 , 31 – 33 ). Therefore, studies should account for general trauma load when investigating CSA-specific effects. Second, it remains challenging to disentangle structural brain changes associated with CSA from those associated with psychopathology. Studies including CSA survivors who meet the criteria for specific psychiatric disorders may not provide unbiased findings on CSA effects per se ( 24 , 27 ). Conversely, as CSA is associated with a significant risk for psychiatric illness, such as MDD, including only psychiatrically healthy survivors of CSA would introduce a bias. Findings from healthy, maltreated individuals might underestimate the effects of CSA and confound findings with brain alterations associated with resilience to CM ( 27 , 34 ). Studies investigating specific CSA effects should therefore include CSA survivors with and without a history of psychiatric illnesses and account for diagnosis effects. In sum, we have an insufficient understanding of the specific effects of CSA on brain morphometry, as previous studies are primarily based on small sample sizes, and specific methodological considerations remain unaddressed. Previous work has repeatedly called for the replication of CSA-specific brain imaging studies and the consideration of trauma load ( 4 , 6 ). Here, we utilize the data from the large German FOR2107 consortium, which investigates the neurobiology of major psychiatric disorders ( 35 ). This trauma-enriched cohort allows for the granular investigation of CSA effects. Using this deeply phenotyped sample, we are uniquely positioned to implement a study design that can compare individuals with CSA to a) non-sexually maltreated individuals and b) non-maltreated individuals. Our groups are carefully matched 1:1 regarding trauma load (in maltreated groups), age, diagnostic group (healthy and depressed), and sex distribution to identify unique effects of CSA on cortical thickness and GMV. Methods and Material Sample N =585 healthy and depressed participants from a total cohort of n = 2039 were selected for the current study. We compared three groups of participants, matched 1:1, each n = 195: 1) CSA , 2) other forms of CM but not CSA ( nCSA ), and 3) no experience of CM ( nCM ). The three groups were age, sex, and MDD diagnosis-matched to the CSA group. Participants were drawn from the Marburg-Münster Affective Disorder Cohort Study (MACS), a bi-center cohort study and part of the FOR2107 consortium investigating the neurobiology of major psychiatric disorders ( 35 ). Participants were White, with Central-European ancestry, aged 18-65, and were recruited via newspapers, advertisements, and flyers. Patients were additionally recruited from in- and out-patient departments of the German universities of Marburg and Münster, as well as local German psychiatric hospitals. Participants were phenotyped using a comprehensive questionnaire battery, neuropsychological assessment, neuroimaging, and collection of biomaterials (see ( 35 ) for a detailed description). Trained staff applied the German version of the structured clinical interview (SCID-I) for the DSM-IV-TR ( 36 ). Exclusion criteria included substance dependence, neurological or other severe somatic disorders, traumatic head injury, a verbal IQ ≤ 80 (assessed using the multiple-choice vocabulary test, MWT-B ( 37 )), and MRI contraindications (e.g., pregnancy, ferromagnetic implants, claustrophobia). Individuals with and without a history of MDD were included. Individuals classified as psychiatrically healthy did not meet the criteria for any current or past psychiatric disorders according to DSM-IV-TR. Participants gave written, informed consent and received financial compensation. The study protocols were approved by the local Ethic Committees in Marburg and Münster, Germany, per the declaration of Helsinki. Assessment of CM Maltreatment experienced during childhood was assessed retrospectively using the German version of the Childhood Trauma Questionnaire (CTQ) ( 38 ). This self-report questionnaire assesses CM across five subscales (physical neglect, emotional neglect, physical abuse, emotional abuse, and sexual abuse) with 25 items, 5 per subscale, summed up to a CM sum score, ranging from 25 - 125. The CTQ further includes three additional items assessing minimalization and denial. Items are rated on a 5-point Likert scale, with higher scores indicating more severe or frequent maltreatment. Individuals were grouped in the CSA group when the validated cut-off score for the sexual abuse subscale was met (sexual abuse ≥ 8) ( 30 ). Sexual abuse scale items included both touch and non-touch experiences of sexual abuse. When individuals met any other maltreatment subscale cut-off score (physical abuse ≥ 8, emotional abuse ≥ 10, physical neglect ≥ 8, emotional neglect ≥ 15), while the CSA criterion was not met, individuals were classified as nCSA (non-sexual forms of maltreatment) ( 30 ). If none of the cut-off scores were met, individuals were classified as nCM (no form of CM). Sample selection and matching In the cohort of n = 2039, n = 204 met the criteria for CSA, while n = 795 were classified as non-sexually maltreated ( nCSA ), and n = 1040 were classified as non-maltreated ( nCM ) according to cut-off scores. We then matched the nCSA and nCM group 1:1 to the CSA group regarding age, sex, diagnostic group, and, in the case of nCSA , general trauma load (CTQ sum score). Matching for trauma load proved difficult, as individuals with CSA ( M = 59.28, SD = 18.48) reported significantly higher CTQ sum scores compared to the nCSA group ( M = 45.45, SD = 11.03). As a result, we were unable to match non-sexually abused individuals to the entire CSA group ( n =204), albeit drawing from a sample of n =795 non-sexually abused individuals. This finding is in line with previous observations that CSA is associated with higher general trauma load ( 30 ). To achieve successful matching, one of our main objectives, we excluded n =9 CSA individuals who reported the most severe CM (CTQ sum scores > 93, with 125 being the maximum). Our final sample included N = 585 individuals with n = 195 each in the CSA , nCSA, and nCM groups; see Figure 1 for the three groups and applied comparisons, and Figure 2 below for sample selection. Download figure Open in new tab Figure 1: Visualization of the three groups, possible comparison outcomes and interpretation of possible group comparisons. Download figure Open in new tab Figure 2: Sample selection and analysis pipeline The final CSA sample ( n = 195) was comprised of mostly women (86%) and patients with MDD (77%), with a mean age of 41.5 years; a naturalistic representation of the actual distribution of CSA in men and women and its effects on mental health ( 6 , 7 ). Group comparisons The goal of this study was to identify unique neural correlates of CSA, while accounting for confounding factors such as trauma load, depression diagnosis, age, and sex. To this end, we chose a 1×3 design with three matched groups: CSA , nCSA , and nCM . Comparisons between the three groups enables a comprehensive understanding of CSA-specific neural correlates, i.e., qualitative maltreatment subtype differences ( CSA vs. nCSA ), broader impact of CSA on the brain ( CSA vs. nCM ), and general maltreatment effects ( nCSA vs nCM ) in individuals with and without a history of depression. Contrasting findings from these three group comparisons allow for a deeper understanding which brain alterations are shared or unique in CSA and other types of CM ( Figure 1 ). To avoid confounding effects of MDD, the nCM group does not constitute a “traditional” healthy control group, as this group was also matched to CSA group characteristics and includes mostly women and individuals with a history of MDD. Our framework ensures that findings are not misattributed to general trauma load, psychopathology, or shared maltreatment effects, making it uniquely powerful to disentangle the complex relationships between maltreatment types, trauma load, and neurodevelopmental outcomes. MRI data acquisition and preprocessing In Marburg and Münster, Germany, high-resolution T1 images were acquired with a 3T whole-body MRI scanner (Marburg: 12-channel head matrix Rx-coil, Tim Trio, Siemens, Erlangen, Germany; Münster: 20-channel head matrix Rx-coil, Prisma, Siemens, Erlangen, Germany) ( 39 ). Parameters of the 3D-fast gradient echo sequence (MPRAGE) varied between sites. Marburg: field of view (FOV) = 256 mm, 176 sagittal slices, repetition time (TR) = 1900 ms, echo time (TE) = 2.26 ms, inversion time (TI) = 900 ms, slice thickness = 1 mm, voxel size = 1 × 1 × 1 mm, flip angle = 9°, Münster: FOV = 256 mm, 192 sagittal slices, TR = 2130 ms, TE = 2.28 ms, TI = 900 ms, slice thickness = 1 mm, voxel size = 1 × 1 × 1 mm, flip angle 8°. Preprocessing was performed by applying default parameters of the CAT12 toolbox (build 1184, Gaser, Structural Brain Mapping Group, Jena University Hospital, Jena, Germany) implemented in SPM12 (v7771, Statistical Parametric Mapping, Institute of Neurology, London, UK) running under MATLAB (version v2017a, The MathWorks, USA). Images passed individual quality control, with a senior researcher manually checking for artifacts, abnormalities, and image quality. Brain images were segmented into gray matter, white matter, and cerebrospinal fluid and then normalized using an adopted DARTEL algorithm ( 40 ). For data smoothing, 8-mm (for GMV) and 20-mm (for cortical thickness) full-width half-maximum Gaussian kernels with an absolute threshold of 0.1 were applied. Statistical analyses Nearest Neighbor matching (using the MatchIt package 4.5.0) was performed to match group sizes 1:1 to the smallest group ( CSA ) regarding age, sex, diagnostic group, and, in the case of the nCSA group, CTQ sum score ( 41 ). All non-brain statistical analyses were performed using R (R Core Team (2021), version 4.1.2). To assess group differences in demographic data, analysis of variance (ANOVA) with subsequent post-hoc Tukey Honest Significant Differences (TukeyHSD) tests were conducted for continuous variables and Pearson’s chi-squared test with subsequent post-hoc analyses based on the residuals were computed for categorical variables (see Table 1 ). To further evaluate differences and comparability between the groups, Bayesian factor analysis was conducted to quantify evidence for the null and alternative hypothesis (see Table 1 and Supplementary Table 1). Here, Bayesian ANOVA was performed to evaluate evidence for group effects in continuous variables, and Bayesian contingency table analysis was applied for categorical variables. View this table: View inline View popup Table 1 Sample Characteristics (N=585) Brain structural analyses We compared GMV and cortical thickness in the three groups ( CSA , nCSA , nCM ). For the voxel-based morphometry (VBM) analyses investigating GMV, we implemented whole-brain analysis of covariance (ANCOVA) models using a full-factorial design in SPM, including the covariates age, sex, diagnosis, total intracranial volume (TIV) and, per our MRI quality assurance protocol, gradient coil and body coil changes in Marburg, which also account for site effects ( 39 ). For the surface-based morphometry (SBM) analyses investigating cortical thickness, we used the CAT12 toolbox (CAT12.8.2, version r2159) that builds on SPM with the same basic model and covariates as in the VBM analyses, without TIV as a covariate. For both modalities, we used threshold-free cluster enhancement (TFCE), a non-parametric multiple-comparison correction, using the TFCE Toolbox (version r264) ( 42 ). We applied the Smith Method with 20,000 permutations and subsequent family-wise error (FWE) correction for multiple comparisons. Results were considered significant at α < 0.05. Anatomical labeling of clusters was performed using the Dartel space Neuromorphometrics atlas implemented in SPM12 for voxel-based morphometry analyses and the Desikan-Killiany DK40 atlas for surface-based morphometry analyses ( 43 ). Although TFCE does not allow for the extraction of effect sizes, we converted TFCE values to t-values, which we then converted to Cohen’s d effect sizes to obtain approximate effect sizes of significant effect. We note that this is an approximation, and these values only represent the peak-voxel, and actual effects might be smaller. Results The final sample included 585 participants (mean age = 41.4, SD = 13.49 years), with 195 participants per group ( CSA, nCSA, and nCM ). Clinical and demographic characteristics are shown below in Table 1 . Matching was successful, as indicated by no significant differences in the groups in age, sex, and diagnosis distribution. CSA and nCSA did not significantly differ in their CTQ sum scores. Compared to the CSA group, the nCSA group was characterized only by significantly lower sexual abuse and higher emotional neglect and abuse (Supplementary Table 1). As shown in the sample characteristics below, the behavioral outcomes demonstrated a pervasive, adverse effect of CM that is sustained even when diagnosis is accounted for. The CSA and the nCSA groups show significantly higher self-reported and rater-based depressive symptoms, higher perceived stress, higher experiences of negative stressful life events, lower social support, lower resilience, fewer years of education, and lower global functioning compared to the nCM group (see Table 1 ). This is further supported by large Bayesian factor scores (>10) in multiple adverse outcomes. These findings align with current literature ( 44 , 45 ). GMV analyses To identify CSA specific GMV alterations, we first compared the CSA to the nCSA group. Second, we investigate results of the CSA vs. nCM comparison and contextualize findings using the nCSA vs. nCM group comparison. Covariates in all models include age, sex, diagnosis, site, and TIV. We first describe findings for positive contrasts for the three comparisons, and then the negative contrasts. We describe clusters with k > 100 voxels here, a full list of all significant results can be found in the Supplement. CSA > nCSA The CSA group exhibited significantly larger GMV in the right exterior cerebellum ( k =1225, TFCE=917.92, p FWE =0.025, x/y/z=33/-48/-32) compared to the nCSA group ( Figure 3A , Supplementary Table 2. The approximate effect size for this effect (converted from t-statistic), is d =0.38, indicating a small effect. These findings may signify brain alterations due to qualitative maltreatment experiences. To further describe respective findings, we explored eigenvariate values for all three groups (Supplementary Figure 1). Significant differences cluster emerged only in the CSA > nCSA comparison, whereas nCSA and CSA do not differ significantly in GMV compared to nCM in the respective comparisons. These findings indicate nuanced differences in the right cerebellum dependent on maltreatment subtype. Download figure Open in new tab Figure 3: Clusters exhibiting significantly larger GMV (TFCE, p FWE -corrected) in A CSA CSA > nCM Compared to the nCM group, the CSA group exhibited larger GMV in the bilateral anterior cingulate gyrus and bilateral superior medial frontal gyrus (mSFG) ( k =842, TFCE=1007.25, p FWE =0.024, x/y/z=-04/46/12, Figure 3B , Supplementary Table 3). The approximate effect size for this effect (converted from t-statistic), is d =0.41, indicating a small effect. Similar regions were detected for the nCSA > nCM comparison, indicating possible general maltreatment effects when comparing individuals with and without MDD. nCSA > nCM The nCSA group exhibited larger GMV in seven large clusters, including the bilateral superior frontal gyri, the bilateral middle cingulate gyri, bilateral pre- and postcentral gyri ( Figure 3B , Supplementary Table 4). Cluster 1: k =10619, TFCE=1386.31, p FWE =0.004, x/y/z=-06/21/63; Cluster 2: k =859, TFCE=1067.21, p FWE =0.018, x/y/z=32/-04/60; Cluster 3: k =989, TFCE=1048.91, p FWE =0.020, x/y/z=-27/00/51; Cluster 4: k =1288, TFCE=1041.91, p FWE =0.021, x/y/z=30/38/-10; Cluster 5: k =781, TFCE=957.70, p FWE =0.031, x/y/z=-48/20/00; Cluster 6: k =316, TFCE=883.27, p FWE =0.045, x/y/z=09/-46/26; Cluster 7: k=175, TFCE=874.00, p FWE =0.047, x/y/z=02/33/-15. These findings may indicate brain changes in non-sexual forms of CM in a population of individuals with and without MDD. CSA < nCM; CSA < nCSA; nCSA 0.05. To rule out possible underlying sex or diagnosis effects interacting with the groups and driving our findings, we ran sex and MDD diagnosis (dichotomous HC vs. MDD) interaction analyses. These analyses revealed no significant interaction effects on GMV. The results suggest that neither MDD diagnosis nor sex impact the significant findings. Moreover, we investigated the potential influence of comorbidity on the observed differences in GMV. To this end, we repeated the analyses, including comorbidity (dichotomous, no vs. yes) as an additional covariate, yielding similar results. This indicates that comorbidity does not account for the observed effects (Supplementary Figure 2 with Supplementary Table 5 - 7). Cortical thickness analyses Analogously to GMV, we compared the CSA to the nCSA group to identify specific alterations in cortical thickness related to CSA. Next, we investigated results of the CSA vs. nCM , and contextualized findings using the nCSA vs. nCM comparison (see Supplement). Covariates in all models include age, sex, site, and diagnosis. We first describe findings for positive contrasts for the three comparisons, and then the negative contrasts. We describe clusters with k > 100 voxels here, a full list of all significant results can be found in the Supplement. CSA > nCSA We identified three clusters of larger cortical thickness in the CSA group compared to the nCSA group, encompassing regions of the bilateral superiorfrontal gyrus, pre- and postcentral gyri, supramarginal gyrus, superior parietal cortex, precuneus and insula (Cluster 1: k =11517, TFCE=19182.83, p FWE =0.011, x/y/z=31/20/08; Cluster 2: k =13137, TFCE=16037.30, p FWE =0.017, x/y/z=-21/-83/39; Cluster 3: k =246, TFCE=9500.77, p FWE =0.049, x/y/z=06/44/26) ( Figure 4A ). Supplementary Table 8 lists all clusters and their respective atlas region. Approximated Cohen’s d effect sizes were Cluster 1: d =0.39, Cluster 2: d =0.37, and Cluster 3: d =0.22, all indicating small effects. These findings may signify brain alterations due to qualitative maltreatment experiences. Download figure Open in new tab Figure 4: Clusters exhibiting significantly larger cortical thickness (TFCE, p FWE - corrected) in CSA compared to A nCSA and B nCM . CSA > nCM The CSA group exhibited greater cortical thickness compared to the nCM group in two clusters encompassing bilateral superiorfrontal, supramarginal, superior temporal, and inferior parietal regions in addition to the insula (Cluster 1: k =13400, TFCE=27566.17, p FWE =0.005, x/y/z=-29/04/54; Cluster 2: k =6478, TFCE=18517.88, p FWE =0.018, x/y/z=63/-40/24) ( Figure 4B ). Supplementary Table 9 lists all clusters and their respective atlas region. The approximated Cohen’s d effect sizes were Cluster 1: d =0.37, and Cluster 2: d =0.35, indicating small effect sizes. nCSA > nCM There was no significant finding for cortical thickness for this comparison, p > 0.05. CSA < nCSA; CSA < nCM; nCSA 0.05. Significant clusters in the CSA > nCSA and CSA > nCM comparisons largely overlapped, indicating possible unique cortical thickness effects that distinguish CSA from both nCSA and nCM . The identified clusters in cortical thickness have been previously associated with major depression ( 46 ). To further explore these findings, we conducted additional exploratory analyses, including the Hamilton rating scale for Depression (HAMD) score as a covariate to investigate if depression severity impacted our findings. When accounting for depression severity, significant differences in cluster sizes between CSA vs. nCSA diminished, whereas differences between CSA and nCM became more pronounced (Supplementary Figure 3, Supplementary Table 10 and 11). This points to an interaction effect of depression severity and maltreatment type for cortical thickness. As with GMV, we investigated possible interaction effects of sex or MDD diagnosis (dichotomous HC vs. MDD) by maltreatment group. Interaction analyses revealed no significant effects. Furthermore, we investigated the potential influence of comorbidity on the observed differences in cortical thickness. To this end, we included comorbidity (dichotomous, no vs. yes) as an additional covariate in the model, which yielded similar results, indicating that comorbidity does not influence the observed effects (Supplementary Figure 4, Supplementary Table 12 and 13). In summary, our findings suggest that CSA is characterized by larger cortical thickness in frontoparietal areas and larger cerebellar GMV when compared to individuals with non-sexual forms of maltreatment. Discussion This is the first to date to directly compare sexually maltreated individuals to non-sexually maltreated individuals with matched trauma loads. This comparison enabled us to detect unique CSA effects, as differences are likely to arise from differences in qualitative maltreatment experiences, while controlling for trauma load, age, sex, and diagnosis. We further investigated whether both groups showed distinct alterations in brain morphology when compared to non-maltreated individuals. Our findings add new, important insights to the extant literature by providing a large sample with matched groups. We identified a unique neural signature of childhood sexual abuse, evident in larger cerebellar GMV and widespread greater cortical thickness in frontoparietal brain areas compared to non-sexually maltreated individuals in a population with and without depression. Importantly, while cortical thickness findings were widespread, the effect sizes for both cortical thickness and GMV were small. Regarding gray matter volume, larger cerebellar GMV distinguished CSA from nCSA , but no significant group differences were found when comparing the maltreated groups to the non-maltreated groups. This observation suggests that while there are discernible differences in cerebellar GMV when comparing CSA to nCSA , these changes do not extend to a broader contrast with a non-maltreated control group. Therefore, any conclusions about the specific impacts of non-sexual maltreatment on cerebellar volume must be tempered by the understanding that these effects might not be as pronounced or detectable when compared to a general control population with comparable age, sex distribution and diagnosis status. The cerebellum has been implicated in social, cognitive, and emotional processes in addition to motor control ( 47 – 50 ). It modulates movement by regulating force, rate, rhythm, and accuracy via error-based learning ( 47 , 51 – 55 ). Given the homogeneous cytoarchitecture of the cerebellum, this error-predictive function might also extend to cognitive and emotional domains ( 47 ). Structural and functional alterations in the cerebellum have been associated with a general vulnerability for multiple mental disorders and general psychopathology ( 56 – 62 ). Previous studies have identified functional cerebro-cerebellar connections, especially those involved in fear and anxiety networks, including the anterior cingulate cortex (ACC), insula, inferior frontal gyrus, amygdala, hippocampus, raphe nuclei, and ventral tegmental area ( 63 – 70 ). Consequently, trauma-induced cerebellar alterations may set the ground for a variety of psychiatric disorders. Several studies have described morphometric cerebellar alterations in association with CM with distinct findings in specific subgroups (e.g., psychiatric diagnosis, CM subtype, children vs. adults) ( 71 – 73 ). Interestingly, two studies indicate that trauma involving extreme physical threat is associated with larger cerebellar volume: female rape survivors with PTSD exhibited increased gray matter density in the left cerebellum, and larger cerebellar GMV was detected in combat-exposed male soldiers ( 74 , 75 ). Our findings of larger cerebellar volume align with these results and point to a possible neural signature of larger cerebellar volume associated with physical threat trauma types. Compared to the nCM group, CSA showed uniquely larger GMV in the bilateral anterior cingulate gyrus and bilateral superior medial frontal gyrus. Similarly, the nCSA > nCM comparison revealed larger GMV in similar regions, which strengthens our assumption of a general trauma effect, rather than a CSA-specific effect. These findings do not align with the current meta-analysis on structural CM effects, which reported no converging evidence for regions with larger GMV in CM survivors ( 1 ). Results from our primarily female, high CM load, and largely depressed sample may reveal unique alterations that do not generalize across all survivors of CM. Of note, in a study of maltreated individuals with and without MDD, larger volume in the maltreated group in the right dorsomedial prefrontal cortex was reported, aligning with our results ( 76 ). Examining cortical thickness, larger cortical thickness compared to nCSA was found in areas encompassing the pre- and postcentral gyrus, the anterior cingulate gyrus, insula, precuneus, superiorfrontal, superiorparietal, and superiortemporal gyri. The findings can further be contextualized using the CSA > nCM comparison. CSA showed similar findings when compared to nCM, with overlap in all these clusters. These results highlight the unique neural correlates of CSA compared to nCSA and nCM , apparent in larger cortical thickness in widespread frontoparietal regions. Smaller cortical thickness is commonly associated with increased psychopathology. In MDD specifically, smaller cortical thickness was reported in the bilateral medial orbitofrontal cortex, fusiform gyrus, insula, rostral anterior and posterior cingulate cortex and in the left middle temporal gyrus, right inferior temporal gyrus, and right caudal ACC ( 77 ). As our sample, including the nCM group, mainly consisted of depressed individuals, cortical thinning should be the present in all three groups ( CSA, nCSA, nCM ). Consequently, our findings possibly suggest a preserved cortical thickness in CSA compared to nCSA and nCM . However, the preserved cortical thickness in CSA does not translate to reduced psychopathology, as indicated by comparable MDD duration and illness onset in the CSA and nCSA groups. When adjusting for depression severity using HAMD, differences in cortical thickness between the CSA and nCSA groups became less pronounced in some regions (right insula, right precentral gyrus and left precuneus and cuneus), whereas the differences between CSA and nCM were more clearly defined (See Supplementary Figure 3 and Supplementary Table 10 and 11). This suggests that while depression severity modulates some of the neural impacts of CSA, particularly when compared with other forms of maltreatment, the core neurobiological alterations associated with CSA remain distinct and robust against a control group without maltreatment. These results underscore the importance of considering both the specific type of maltreatment and the role of concurrent psychiatric symptoms in understanding their differential impacts on brain structure. Our findings do not align with previous findings reporting smaller cortical thickness in the somatosensory cortex in a sample of younger women with CSA ( 26 ). This difference is likely due to variations in sample characteristics, including age, as well as sample sizes and different analytical approach ( 11 ). Importantly, while previous studies have primarily focused on younger adults where trauma occurred more recently, our study examines a middle-aged sample with a mean age of 41.5 years. This represents a significant and necessary expansion of previous research, demonstrating that even decades after the trauma, CSA continues to exert measurable effects on the brain. Our findings highlight the value of studying later-life populations, as they provide unique insights into the prolonged impacts of CSA on brain over time ( 11 ). To summarize, this study advances our understanding of the unique morphometric effects of CSA. First, our sample represents the full range of affected individuals, including healthy and depressed men and women with an extensive age range. Second, we have provided the largest study sample so far, including 195 individuals with a history of CSA. Third, we have implemented a methodologically novel approach, by matching groups according to trauma load, age, sex, and MDD diagnosis distribution. Some limitations regarding our study design must be noted. While the rigorous matching procedure allowed us to investigate the specific effects of CSA exposure, it naturally led to an artificially high number of women and MDD patients in the nCSA and nCM comparison groups. Moreover, it resulted in a relatively high trauma load in the nCSA group. Together, these matched groups generally impede direct comparability to previous findings. Owing to our sample characteristics, we focused on individuals with and without MDD. It is important to note that CSA is also associated with higher rates of other psychiatric illnesses, such as anxiety, PTSD, and substance misuse ( 6 ). Future studies should investigate effects of CM in these populations to provide a more comprehensive understanding of the impacts of CSA and differential psychopathology on brain morphometry. Retrospective self-report measures for CM may be influenced by recall bias, with studies indicating differences between prospective and retrospective reports ( 78 , 79 ). Nevertheless, the CTQ has shown good temporal stability ( 80 ). Recent meta-analytic findings suggest that retrospective measures exhibit a stronger association with psychopathology than prospective measures ( 81 ). Further, the CTQ does not assess the age at which maltreatment occurred, preventing the analysis of timing-specific effects that have been linked to varying brain outcomes in several studies ( 10 , 16 , 82 ). Moreover, as with all cross-sectional designs, we cannot infer causality. It is possible that, as discussed by Blithikori et al. (2022) trauma-related morphometric changes are secondary to biological, psychological, or environmental factors that are not caused by, but rather associated with, CSA ( 57 ). Our findings, using a carefully matched group design, indicate a difference in sexual vs. non-sexual abuse apparent in cortical thickness in widespread fronto-parietal areas and larger cerebellar GMV, even when controlling for general trauma load. While these brain changes may relate to adverse outcomes in the long-term, they may initially represent an adaptive response to highly adverse environments and a short-term survival strategy which are specific to the type of trauma experienced ( 4 ). Future studies should use longitudinal designs to further explore the impact of CSA on structural and functional connectivity, and their association with behavioral phenotypes. Given the pronounced effects of CM, and CSA specifically, mental health initiatives should focus on large-scale preventative measures and foster protective factors that can mitigate the deleterious effects of CM. Data Availability All data produced in the present study are available upon reasonable request to the authors Funding This work is part of the German multicenter consortium “Neurobiology of Affective Disorders. A translational perspective on brain structure and function”, funded by the German Research Foundation (Research Unit FOR2107 and CRC 393). Principal investigators are Tilo Kircher (KI588/14-1, KI588/14-2, KI588/20-1, KI588/22-1), Udo Dannlowski (DA1151/5-1, DA1151/5-2), Axel Krug (KR3822/5-1, KR3822/7-2), Igor Nenadić (NE2254/1-2, NE2254/2-1, NE2254/3-1,NE2254/4-1), Carsten Konrad (KO4291/3-1), Benjamin Straube (STR1146/18-1). The study was in part supported by grants from UKGM and Forschungscampus Mittelhessen to Igor Nenadić and the Hessian Ministry of Higher Education, Science, Research and Art (LOEWE project “DYNAMIC”) to Tilo Kircher, Nina Alexander, Igor Nenadić and Benjamin Straube. This research also partly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation): TRR 289 Treatment Expectation—Project Number 422744262. Disclosures TK received unrestricted educational grants from Servier, Janssen, Recordati, Aristo, Otsuka, and neuraxpharm. This funding is not associated with the current work. All other authors report no conflicts of interest. CRediT authorship contribution statement KB, VH: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project Administration, Writing – original draft. PU, FSt , SZ , FSch , FTO , LT , SM , KT , KF , NS , JG , EL, LB , DG, NW, ED: Data curation, Writing – review & editing. TH , BS , HJ , AJ , AK , DU , IN, TK: Funding Acquisition, Writing – review & editing. NA: Conceptualization, Funding Acquisition, Methodology, Supervision, Writing – review & editing. Acknowledgements The FOR2107 cohort project was approved by the Ethics Committees of the Medical Faculties, University of Marburg (AZ:07/14) and University of Münster (AZ:2014-422-b-S). We are deeply indebted to all study participants and staff. A list of acknowledgments can be found here: https://for2107.de/acknowledgements/?lang=en . References 1. ↵ Yang W , Jin S , Duan W , Yu H , Ping L , Shen Z , et al. The effects of childhood maltreatment on cortical thickness and gray matter volume: a coordinate-based meta-analysis . Psychol Med [Internet ]. 2023 Mar 22 [cited 2023 Sep 22]; 53 ( 5 ). Available from: https://pubmed.ncbi.nlm.nih.gov/36946124/ 2. ↵ Madigan S , Deneault AA , Racine N , Park J , Thiemann R , Zhu J , et al. 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