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Psychiatry Investig > Volume 23(6); 2026 > Article
Kim, Kim, and Lee: Interaction Effect of Panic Disorder Diagnosis and Early Trauma History on Cortical Gyrification Patterns

Abstract

Objective

Early trauma (ET) occurring during critical periods of brain development has been associated with structural brain alterations. ET history and structural brain changes have been linked to panic disorder (PD). Abnormalities in cortical gyrification patterns have been reported in both patients with PD and individuals with a history of ET. This study aimed to examine the interaction between ET history and PD diagnosis in relation to cortical gyrification patterns.

Methods

The study included 83 patients with PD and 83 age- and sex-matched healthy controls. High-resolution T1-weighted brain images were analyzed using vertex-based methods to evaluate the local gyrification index (LGI). ET history was assessed using the Early Trauma Inventory Self-Report Short Form. Anxiety symptomatology was evaluated using the Panic Disorder Severity Scale (PDSS) and the Intolerance of Uncertainty Scale (IUS).

Results

A significant interaction between PD diagnosis and ET history was observed in the LGI of the gyrus portion of the superior parietal lobule (SPL). Patients with PD who had experienced ET showed significantly higher LGI values in the SPL than those without ET. SPL LGI values were positively correlated with PDSS and IUS total scores across all participants.

Conclusion

These findings suggest an interaction effect of PD diagnosis and ET history on cortical gyrification alterations in the SPL. The results underscore the importance of considering both ET and brain structural characteristics when investigating the pathophysiology of PD. Further studies are warranted to elucidate the mechanisms linking ET, cortical gyrification, and PD.

INTRODUCTION

Panic disorder (PD), which affects approximately 4% of the global population, is a major psychiatric condition characterized by recurrent panic attacks and marked behavioral changes [1]. Although its etiology remains incompletely understood, PD is believed to have a multifactorial origin, with early traumatic experiences in childhood potentially contributing to its development [2]. Although the etiopathological relationship between early trauma (ET) and PD is not yet fully clarified, previous studies have suggested that ET may trigger chronic stress responses that disrupt brain development during developmental periods and, consequently, increase vulnerability to PD in adulthood [3,4].
Although information on this etiopathological link remains limited, structural and functional neuroimaging studies have demonstrated that a history of ET can alter both brain structure and function, thereby heightening susceptibility to PD. Specifically, one functional neuroimaging study found that childhood trauma was associated with altered resting-state functional connectivity within the fear network model in patients with PD [5]. In addition, a structural neuroimaging study identified an association between ET and alterations in the fornix body among patients with PD [6]. Moreover, another study reported an interaction effect on cortical thickness in the insula and pars triangularis when considering the combined impact of PD diagnosis and ET exposure [7]. Given that both functional connectivity5 and white matter structures6 have been reported as neurobiological correlates of ET in PD, it remains unclear whether cortical gyrification reflects ET-related alterations in this disorder.
Cortical gyrification, quantified by the local gyrification index (LGI), reflects higher-order cortical folding and has been associated with other structural characteristics of the brain, including cortical thickness [8] and connectivity [9]. Alterations in cortical gyrification have been implicated in various anxiety disorders, such as PD [10] and generalized anxiety disorder [11]. Gyrification begins in the prenatal stage and continues to develop throughout early life. Gyri form as regions with greater neural connectivity move closer together, whereas sulci develop as regions with weaker connectivity diverge [9]. Earlier, gyrification patterns were thought to be largely established during early development; however, recent studies suggest that environmental factors during childhood and adolescence can meaningfully influence these patterns [9]. Accordingly, ET, as an environmental factor, may also affect gyrification. Because gyrification is considered a relatively stable neurodevelopmental marker, examining its interaction with ET exposure and PD diagnosis may provide valuable insights into neurodevelopmental vulnerabilities and inform early intervention approaches.
The effects of ET on cortical gyrification in adolescents have produced inconsistent results. For example, one study reported reduced gyrification in the lingual gyrus, insula, and pars opercularis among maltreated individuals [12], whereas another study found increased LGI in the superior parietal lobule (SPL) of the left hemisphere [13]. These discrepancies may stem from differences in the types of ET experienced by participants across studies, with the former involving more cases of physical abuse than the latter. Furthermore, comparisons between patients with PD and healthy controls (HCs) revealed significant gyrification differences, characterized by reductions in lateral cortical regions and increases in posteromedial areas [10]. Given the established evidence that ET can modify brain structure and enhance vulnerability to PD, it is plausible that ET induces gyrification changes that contribute to PD development.
The combined influence of childhood abuse and PD on cortical gyrification has not been extensively investigated. This study aims to enhance understanding of how ET contributes to the pathophysiology of PD through alterations in cortical gyrification. We hypothesize that individuals with a history of ET will display distinct gyrification patterns in PD compared with HCs. Furthermore, we hypothesize that gyrification in specific cortical regions will correlate with anxiety-related scale scores, thereby clarifying the interrelationship among ET, PD, and cortical gyrification.

METHODS

Study participants

Eighty-three patients with PD were recruited from CHA Bundang Medical Center (Seongnam, Republic of Korea) between December 2013 and June 2022. HCs were recruited from the local community through print advertisements between July 2016 and September 2022. A total of 83 age- and sexmatched HCs were included in the study. All participants were aged 19-64 years and right-handed. Handedness was assessed using the Edinburgh Handedness Inventory [14].
The clinical diagnosis of PD was determined using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (DSM) disorders, based on the diagnostic criteria of either DSM, Fourth Edition, Text Revision or DSM, Fifth Edition [15,16]. Exclusion criteria included any current or past psychiatric disorders—such as anxiety, mood, or psychotic disorders—other than PD in the patient group. Participants with major medical or neurological disorders were also excluded. Additional exclusion criteria comprised contraindications to MR, intellectual disability, other neurological disorders, traumatic brain injury, pregnancy, and left-handedness.
All patients with PD had received psychotropic medications, including selective serotonin reuptake inhibitors (SSRIs) such as sertraline, paroxetine, fluoxetine, or escitalopram. Benzodiazepines were prescribed as needed (pro re nata). The treatment regimen followed the 2008 Korean Medication Algorithm for PD [17]. All study procedures were reviewed and approved by the Institutional Review Board of CHA Bundang Medical Center (IRB No. 2019-05-030) in accordance with the latest version of the Declaration of Helsinki and the principles of Good Clinical Practice. Written informed consent was obtained from all participants after a detailed explanation of the study objectives and procedures.

Clinical assessments

Early trauma

All participants were assessed for ET history before the age of 18 using the Korean version of the Early Trauma Inventory Self-Report Short Form (ETISR-SF). The ETISR-SF is a validated and reliable instrument, with a Cronbach’s α of 0.803 [18]. This questionnaire comprises 27 dichotomous (“yes” or “no”) items that assess four trauma domains: physical (5 items), emotional (5 items), sexual (6 items), and general (11 items) traumatic experiences. Participants who reported at least one ET event on the ETISR-SF were classified as “exposed,” consistent with previous studies [7,19]. In addition, the ETISR-SF records both the frequency and type of traumatic events. Besides the categorical classification, continuous ETISR-SF scores were also used to confirm the robustness of interaction effects.

Anxiety symptomatology

Panic symptom severity was evaluated using the Panic Disorder Severity Scale (PDSS)-Self Report [20]. The PDSS consists of 7 items rated on a 4-point scale (0-4), corresponding to mild, moderate, severe, and extremely severe [21]. The scale assesses the frequency of panic attacks, distress associated with panic attacks, anticipatory anxiety, agoraphobic fear and avoidance, fear or avoidance of panic-related sensations, and functional impairment in work and social domains [22]. The Korean version of the PDSS has demonstrated adequate internal consistency (Cronbach’s α=0.88) [23].
Furthermore, intolerance of uncertainty—a key cognitive feature related to anxiety—was measured using the Intolerance of Uncertainty Scale-Short Form (IUS-12) [24]. The IUS-12 is a 12-item, two-factor version of the original scale that assesses reactions to uncertainty, ambiguity, and future events [25]. Each item is rated from 1 to 4, yielding total scores ranging from 12 to 48. The Korean version of the IUS-12 has demonstrated high internal consistency (Cronbach’s α=0.842) [26].

Neuroimaging data acquisition and gyrification index analysis

All participants underwent brain MRI scans using a GE Signa HDxt 3.0-Tesla scanner (GE Healthcare) equipped with an 8-channel phased-array head coil. Three-dimensional T1-weighted fast spoiled gradient-recalled echo sequences were acquired with the following parameters: repetition time=6.3 ms; echo time=2.1 ms; flip angle=12°; slice thickness=1 mm; field of view=256×256 mm2; matrix size=256×256; and isotropic voxel size=1×1×1 mm3. Neuroimaging data were processed using FreeSurfer (version 7.4.1). The standard preprocessing pipeline included motion correction, removal of nonbrain tissue using a hybrid watershed/surface deformation algorithm, automated Talairach transformation, segmentation of subcortical white and deep gray matter structures, intensity normalization, tessellation of the gray-white matter boundary, topological correction, and surface deformation to identify optimal boundaries based on the greatest intensity gradients.
LGI was computed as a measure of cortical folding following the method developed by Schaer et al. [27] LGI quantifies three-dimensional surface-based cortical gyrification, minimizing bias related to slice orientation and enabling precise localization of gyral abnormalities. After reconstruction of the pial surface and generation of an outer hull tightly enclosing the cortex, LGI was calculated as the ratio of the areas of vertex-based circular regions between the pial and outer surfaces. LGI values at each cortical vertex represent the proportion of cortex buried within sulcal folds of the surrounding circular region, with higher values indicating greater cortical folding [27]. To localize cortical folding abnormalities, the cerebral cortex was parcellated according to the labeling system of the Destrieux Atlas implemented in FreeSurfer [28]. The LGI values of vertices within each parcellated region were averaged to derive the mean LGI of that subregion. Because the process of obtaining the LGI transforms cortical LGI maps into relatively smooth maps, we did not apply further smoothing [29]. The left and right hemispheres were analyzed separately. Multiple hemispheric testing was controlled using a Bonferroni correction, with the significance threshold adjusted for the two hemispheres.

Statistical analyses

The sociodemographic and clinical characteristics of participants were analyzed using independent t-tests, chi-square tests, and two-way analyses of variance, depending on the variable type.
Interaction effects between ET exposure (exposed vs. unexposed) and diagnosis (PD vs. HC) were examined using wholebrain vertex-based analyses to identify cortical gyrification differences associated with ET exposure between patients with PD and HCs. To correct for multiple comparisons, a clusterwise correction was applied using a Monte Carlo simulation with 10,000 iterations (vertex-wise threshold: p<0.001, twotailed) [29]. To rule out potential medication effects, supplementary sensitivity analyses were conducted after excluding participants with high psychotropic medication exposure, defined as doses at or above the 95th percentile for benzodiazepine equivalents (≥7 mg diazepam equivalent) and SSRI equivalents (≥26 mg fluoxetine equivalent). Furthermore, to evaluate the potential motion proxy effect, sensitivity analyses were conducted by excluding participants with poor surface reconstruction quality, defined as low Euler number values (lower 5%, <-93.3). Multiple linear regression analyses were then conducted with ET exposure treated as a continuous variable (ETISR-SF score), including age, sex, PD diagnosis, ET exposure, and the PD diagnosis×ET exposure interaction term as independent variables.
To examine the relationship between LGI and anxiety symptomatology, mean LGI values from brain regions showing significant PD×ET interaction effects were extracted for each participant. Spearman’s rank correlation coefficients were calculated for nonparametric distributions.
All statistical analyses were conducted using IBM SPSS Statistics version 29.0 (IBM Corp.). Statistical significance was set at p<0.05.

RESULTS

Demographic and clinical characteristics

The demographic and clinical characteristics of participants in the PD (n=83) and HC (n=83) groups are summarized (Table 1). There were no significant differences in age or sex between the two groups. However, HCs had higher educational attainment than patients with PD (p<0.001). No significant differences were found in age, years of education, or medication dosage between participants with and without ET exposure. Among patients with PD, however, PDSS scores were significantly higher in the ET-exposed group than in the unexposed group. The interaction effect of diagnosis and ET exposure showed no differences in age or years of education but yielded significant differences in both PDSS and IUS total scores.

The interaction effects between ET exposure and PD diagnosis on the LGI

Whole-brain vertex-based analysis of LGI revealed significant interaction effects between PD diagnosis and ET exposure in the gyrus portion of the SPL (vertex-wise threshold: p<0.001) (Figure 1). The cluster size for the SPL in the right hemisphere was 1,879.47 mm², with peak vertex Montreal Neurological Institute coordinates at x=20.9, y=-79.7, z=43.0 (cluster-wise corrected p=0.0002). The mean LGI of the SPL was significantly higher in patients with PD and ET exposure than in those without ET exposure. These interaction effects remained significant after adjusting for age, sex, years of education, SSRI use, benzodiazepine use, total intracranial volume, and a head motion proxy (Euler number) as covariates. However, no significant main effects of PD diagnosis or ET exposure on the mean LGI of the SPL were observed. Simple effects analyses demonstrated a large ET-related difference within the PD group (Cohen’s d=0.91, 95% confidence interval [CI] 0.28 to 1.53), whereas a moderate effect in the opposite direction was observed in the HC group (Cohen’s d=-0.46, 95% CI -0.988 to 0.065). The resulting difference-in-difference estimate indicated a large PD diagnosis-by-ET exposure interaction effect (Cohen’s d=1.33, 95% CI 0.53 to 2.14). Consistent with these findings, the partial η² value for the PD-by-ET interaction was 0.062, compared with 0.006 for the main effect of PD diagnosis and 0.005 for the main effect of ET exposure.
Additionally, sensitivity analyses excluding participants with doses at or above the 95th percentile (≥7 mg diazepam equivalent for benzodiazepine equivalents) and (≥26 mg fluoxetine equivalent for SSRIs) yielded comparable results, with the PD diagnosis-by-ET interaction effects on cortical gyrification remaining unchanged (Supplementary Tables 1 and 2). Similar robustness was observed in the sensitivity analyses excluding participants with low Euler number values (lower 5%, ≤-93.3) (Supplementary Tables 3 and 4).
To further examine the influence of PD diagnosis and ET exposure (treated as continuous variables based on ETISR-SF scores) on mean SPL LGI, multiple linear regression analysis was performed across all participants. The model included age, sex, PD diagnosis, ET exposure, years of education, SSRI equivalent dosage, and the PD×ET interaction term as independent variables. The mean SPL LGI was significantly predicted by the PD×ET interaction (F=4.725, p<0.001, adjusted R²=0.178). The result of the multiple regression predicting mean LGI in the SPL are summarized (Table 2). Age (p=0.033), sex (p=0.001), years of education (p=0.003), and the PD×ET interaction (p=0.046) were all significant predictors In addition, ET subtype analyses showed that significant PD diagnosis-by-ET subtype interaction effects in the superior frontal gyrus and supramarginal gyrus for general trauma, the inferior temporal gyrus for emotional trauma, and the insula for sexual trauma (Supplementary Tables 5-7).

Correlational analyses between the LGI in the gyrus portion of the SPL and anxiety symptomatology scores among all participants

Significant positive correlations were found between mean LGI values in the SPL peak region and PDSS scores (Spearman’s ρ=0.164, p=0.036) (Figure 2A), as well as between mean LGI values and IUS scores (Spearman’s ρ=0.171, p=0.029) (Figure 2B) across all participants.

DISCUSSION

To the best of our knowledge, this is the first study to investigate the interaction effects of PD diagnosis and ET exposure on cortical gyrification patterns. Specifically, our findings revealed a significant interaction between PD diagnosis and ET exposure in the SPL. Patients with PD who had experienced ET showed greater cortical gyrification in the SPL than those without ET exposure. In contrast, HCs without ET exposure exhibited higher SPL gyrification than ET-exposed HCs. Furthermore, our result implies that greater SPL gyrification might be associated with higher levels of anxiety symptom severity, including panic symptom severity and intolerance of uncertainty, across participants.
Differences in cortical gyrification patterns observed in neuropsychiatric disorders may reflect dysregulated or immature cortical organization and connectivity [30]. Although earlier research regarded gyrification primarily as a reflection of early developmental and genetic influences [31], more recent evidence suggests that gyrification can continue to change throughout adolescence and adulthood [32]. Among various developmental influences, ET has been particularly associated with alterations in cortical gyrification. For instance, one study demonstrated hypogyrification in the lingual gyrus and insula of children who had experienced maltreatment [12].
In patients with PD, previous studies have reported hypogyrification in the lateral brain regions extending from the frontoparietal to temporal areas and hypergyrification in the posteromedial cortical regions compared with HC [10]. The observed hypergyrification in posteromedial regions has been interpreted as a compensatory mechanism for managing panic symptoms in PD [10]. Moreover, another study found that individuals in the early stages of schizophrenia, mood disorders, and autism spectrum disorder exhibited increased LGI, which later declined by mid-adulthood. This pattern suggests that hypergyrification may represent a transient, stage-dependent alteration occurring during the early phase of illness [30]. Therefore, given the established association between gyrification and cortical connectivity [33], our finding of altered SPL gyrification may indicate abnormalities in connectivity between the SPL and related neural networks.
Previous research on adults with a history of childhood trauma but without neuropsychiatric disorders has reported a negative association between childhood abuse history and both gray matter volume and cortical surface area in the SPL [34]. This study on ET in HCs supports our present findings, as ET-exposed HCs exhibited hypogyrification in the SPL compared with unexposed HCs. Our results revealed distinct SPL gyrification patterns between patients with PD and HCs. In conjunction with a previous study demonstrating an interaction between PD diagnosis and ET exposure on cortical thickness [7], our findings support the notion that ET may exert unique neurodevelopmental effects on individuals with a pre-existing vulnerability to PD.
The SPL, located within the parietal cortex, is involved in visuospatial integration, attentional shifting, and interoceptive processing [35,36]. Individuals exposed to ET consistently exhibited heightened vigilance toward bodily and environmental cues [35,36], which may increase demands on neural systems responsible for integrating visuospatial signals with spatial attention. In this context, the SPL may represent a critical neural substrate underlying the PD diagnosis-by-ET interactions. Furthermore, interoceptive processing appears to be a key mechanism linking SPL function to PD vulnerability. Previous neuroimaging studies have demonstrated that patients with PD show increased SPL activation in response to interoceptive stimuli than HCs, reflecting heightened attentional engagement with and monitoring of internal bodily signals. This altered interoceptive-attentional state may contribute to exaggerated threat interpretations of ambiguous bodily sensations, a core feature of PD. Collectively, given its integrative role across visuospatial processing, attentional shifting, and interoception, the SPL may exhibit compensatory hypergyrification in individuals vulnerable to PD following ET exposure.
Previous studies have demonstrated associations between structural alterations in the superior parietal region and anxiety disorders [11,37,38]. Specifically, patients with generalized anxiety disorder exhibited hypergyrification in the superior parietal region compared with HCs [11]. In patients with PD, altered activation of the bilateral SPL during both interoceptive and exteroceptive perception has also been reported compared with HCs [38].
ET can exert lasting adverse effects on psychological and behavioral functioning, potentially leading to various anxiety disorders [39,40]. Evidence suggests that ET may influence brain structure in patients with PD by increasing resting-state functional connectivity between the insula and thalamus and the parietal and temporal lobes [5]. Prior research has consistently shown that PD is strongly associated with a history of ET [41]. Considering the evidence that ET can alter brain structure in PD [5], it is plausible that ET specifically affects brain morphology in the SPL, thereby heightening vulnerability to PD.
Our study demonstrated that the interaction between PD diagnosis and ET exposure influenced cortical gyrification in the gyrus portion of the SPL and revealed significant correlations between SPL gyrification and both PDSS and IUS scores. Whereas previous literature has reported correlations between LGI values in the posterior cingulate cortex and precuneus and panic symptom severity [10], our findings suggest the possibility of the association of the hypergyrification of the SPL is associated with both panic symptom severity and intolerance of uncertainty.
We propose a neurodevelopmental model of vulnerability to PD, building upon previous studies showing that individuals with high intolerance of uncertainty tend to interpret ambiguous interoceptive signals as threatening [42], and that such ambiguous interoceptive stimuli are particularly likely to be perceived as anxiety-related in patients with PD [43]. The observed crossover interaction suggests that ET may lead to divergent neurodevelopmental outcomes depending on an individual’s underlying vulnerability to PD.
One plausible interpretation of the observed hypogyrification in ET-exposed HCs is that it reflects an adaptive neurodevelopmental process, such as experience-dependent synaptic pruning or accelerated cortical maturation. Previous studies have reported that early adversity may be associated with region-specific reductions in cortical complexity, potentially reflecting neural adaptation rather than pathological disruption of development [12]. In HCs, ET may promote more efficient pruning of neural circuits involved in visuospatial integration and attentional allocation within the SPL, thereby reducing cortical folding and potentially increasing neural efficiency. This adaptive pruning process may confer resilience against maladaptive hypervigilance and excessive interoceptive monitoring [35].
In contrast, while ET may be associated with hypogyrification in HCs, it may exert different neurodevelopmental effects on individuals predisposed to PD, as reflected by the observed hypergyrification of the SPL. We hypothesize that hypergyrification of the SPL may represent a neural substrate underlying dysregulated interoceptive awareness in individuals susceptible to PD, a notion supported by previous findings of increased activation in superior parietal regions during interoceptive perception in patients with PD [40]. This altered interoceptive state, when combined with heightened intolerance of uncertainty, may precipitate the development of PD. Our findings suggest that ET may result in distinct patterns of brain structural alterations in individuals vulnerable to PD compared with those without such susceptibility.
These findings carry several clinical implications. First, ETrelated alterations in SPL gyrification may serve as a potential neuroimaging biomarker for identifying individuals at heightened risk of developing PD following early adversity. Second, although SSRI medication dosages did not differ significantly between groups, and sensitivity analysis excluding participants with high benzodiazepine and SSRI medication doses was conducted, the use of other psychotropic medications may have differed in treatment duration, dosage, or medication history, thereby potentially influencing brain structure. Third, differences in ET subtypes across studies may contribute to inconsistencies in the brain regions associated with ET or PD compared with previous studies [10,12]. However, our results underscore the importance of ET-informed approaches in the assessment and treatment of PD, as the neurobiological impact of ET appears to differ fundamentally between individuals who develop PD and those who do not. Fourth, ET exposure was assessed using the self-report-based ETISR-SF and operationally defined using a binary classification of the presence or absence of ET. Retrospective self-reported measures may be subject to recall bias and may not fully capture the complexity or accuracy of past traumatic experiences. Additionally, defining ET exposure based on endorsement of a single item represents a relatively inclusive threshold and does not account for differences in trauma type or severity. These methodological factors may have influenced the classification of ET exposure and the interpretation of the findings. Future studies with larger samples and prospective designs are needed to examine trauma type- specific and severity-dependent effects to improve the robustness and interpretability of results. Fifth, because SPL hypergyrification may reflect dysregulated interoceptive processing driven by intolerance of uncertainty, patients with PD who have a history of ET may particularly benefit from therapeutic interventions targeting intolerance of uncertainty and interoceptive dysregulation, such as cognitive-behavioral therapy or interoceptive exposure.
In conclusion, our findings indicate that ET exerts distinct effects on brain structure in patients with PD compared with HCs, particularly in the gyrus portion of the SPL. These results suggest that ET may influence neurodevelopmental processes by altering the gyrification pattern of the SPL, thereby increasing vulnerability to PD.

Supplementary Materials

The Supplement is available with this article at https://doi.org/10.30773/pi.2025.0414.
Supplementary Table 1.
Participants across diagnostic and ET subgroups in the sensitivity analysis after excluding high-dose medication users
pi-2025-0414-Supplementary-Table-1.pdf
Supplementary Table 2.
Clusters showing significant PD diagnosis-by-early trauma interaction effects after excluding high-dose medication users
pi-2025-0414-Supplementary-Table-2.pdf
Supplementary Table 3.
Participants by diagnostic and ET subgroups in sensitivity analysis after excluding participants with a low head motion proxy (Euler number ≤-93.3)
pi-2025-0414-Supplementary-Table-3.pdf
Supplementary Table 4.
Cluster showing significant panic disorder diagnosis-by-early trauma exposure interaction effects after excluding participants with low head motion proxy (Euler number ≤-93.3)
pi-2025-0414-Supplementary-Table-4.pdf
Supplementary Table 5.
Clusters showing significant PD diagnosis-by-general early trauma subtype interaction effects
pi-2025-0414-Supplementary-Table-5.pdf
Supplementary Table 6.
Cluster showing significant PD diagnosis-by-emotional early trauma subtype interaction effects
pi-2025-0414-Supplementary-Table-6.pdf
Supplementary Table 7.
Cluster showing significant PD diagnosis-by-sexual early trauma interaction effects
pi-2025-0414-Supplementary-Table-7.pdf

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: all authors. Data curation: Myung Sin Kim, Hyun-Ju Kim. Formal analysis: Myung Sin Kim, Hyun-Ju Kim. Funding acquisition: Sang-Hyuk Lee. Investigation: all authors. Methodology: all authors. Project administration: Sang-Hyuk Lee. Resources: Sang-Hyuk Lee. Software: Hyun-Ju Kim, Sang-Hyuk Lee. Supervision: Hyun-Ju Kim, Sang-Hyuk Lee. Validation: all authors. Visualization: Myung Sin Kim, Hyun-Ju Kim. Writing—original draft: all authors. Writing—review & editing: all authors.

Funding Statement

The Basic Science Research Program supported this research through the National Research Foundation of Korea, funded by the Ministry of Science and ICT [grant number NRF-2021M3E5D9025026].

Acknowledgments

None

Figure 1.
Result of whole-brain vertex-wise analyses evaluating the effect of the interaction between the two factors (ET exposure×PD diagnosis) on LGI. To control for multiple comparisons, cluster corrections were performed using Monte Carlo simulation with 10,000 iterations (vertex-wise threshold of p<0.001). Talairach (Montreal Neurological Institute 305) coordinates of the maximum: the gyrus portion of the superior parietal lobule, x=20.9, y=-79.7, z=43.0. ET, early trauma; LGI, local gyrification index; PD, panic disorder; HC, healthy control.
pi-2025-0414f1.jpg
Figure 2.
Scatter plots of the positive significant correlations between the LGI of gyrus portion of the SPL and (A) PDSS total scores and (B) IUS total scores in this study participants (N=166). LGI, local gyrification index; PDSS, Panic Disorder Severity Scale; IUS, Intolerance of Uncertainty Scale; SPL, superior parietal lobule.
pi-2025-0414f2.jpg
Table 1.
Sociodemographic and clinical characteristics of patients with PD and HCs
PD ET exposed (N=71) PD ET unexposed (N=12) HCs ET exposed (N=65) HCs ET unexposed (N=18) Statistics*
Statistics† diagnosis effects
ET exposure effects
Diagnosis-by-ET interaction effects
t or χ² p F p F p F p
Sex, female 34 (47.9) 10 (83.3) 31 (47.7) 11 (61.1) - - 1.21 0.270 5.76 0.020 1.17 0.280
Age (yr) 36.70±12.43 41.42±11.52 35.51±9.34 38.00±12.02 - - 1.01 0.320 2.46 0.120 0.23 0.630
Education (yr) 14.41±2.27 15.75±2.01 16.92±2.20 16.82±1.88 - - 15.68 <0.001 1.88 0.170 2.53 0.110
Family history of anxiety disorders, yes 17 (24.60) 4 (33.3) 4 (6.8) 1 (6.7) - - 8.19 0.005 0.30 0.580 0.32 0.570
Duration of illness (months) 30.26±37.52 35.50±28.91 - - 0.37 0.71 - - - - - -
Agoraphobia, yes 51 (71.8) 8 (66.7) - - 0.93 0.34 - - - - - -
SSRI equivalent dosage‡ (mg) 10.28±8.52 7.92±5.42 - - 0.92 0.36 - - - - - -
Kind of SSRI
 Escitalopram 29 (40.8) 7 (58.3) - - 1.28 0.26 - - - - - -
 Paroxetine 26 (36.6) 3 (25.0) - - 0.61 0.44 - - - - - -
Benzodiazepine equivalent dosage§ (mg) 0.96±0.84 2.41±2.22 - - 4.0 0.03 - - - - - -
Kind of Benzodiazepine
 Alprazolam 52 (62.6) 9 (75) - - 0.02 0.90 - - - - - -
 Clonazepam 38 (45.8) 3 (25.0) - - 3.34 0.07 - - - - - -
ET (ETISR-SF) 5.92±3.89 0.00±0.00 3.75±2.53 0.00±0.00 - - 3.06 0.230 61.22 <0.001 3.06 0.080
 General trauma 1.63±1.63 0.00±0.00 1.02±1.04 0.00±0.00 - - 1.44 0.080 26.44 <0.001 1.44 0.230
 Physical trauma 2.12±1.65 0.00±0.00 1.94±1.52 0.00±0.00 - - 0.10 0.750 46.82 <0.001 0.10 0.750
 Emotional trauma 1.62±1.71 0.00±0.00 0.66±1.11 0.00±0.00 - - 3.12 0.080 17.68 <0.001 3.12 0.080
 Sexual trauma 0.53±0.97 0.00±0.00 0.13±0.43 0.00±0.00 - - 1.96 0.160 5.64 0.020 1.96 0.160
Panic symptom severity 13.52±6.73 9.33±5.52 0.06±0.39 0.00±0.00 - - 137.62 <0.001 4.79 0.030 4.51 0.040
Intolerance of uncertainty 31.91±6.59 27.27±8.32 24.82±6.10 25.53±5.90 - - 10.45 0.001 2.06 0.150 3.83 0.050

Data are presented as mean±standard deviation or number (%).

* a group comparison was performed between the two groups (patients with PD and HCs);

† group comparisons were conducted across four subgroups defined by diagnosis (PD vs. HCs) and ET exposure (exposed vs. unexposed) using independent two-factor analysis of variance (PD diagnosis, ET exposure, and interaction effects of two factors) to test mean differences, and χ2 statistics were used to analyze frequencies;

‡ SSRI equivalent dosage, 10 mg of escitalopram=12.5 mg of paroxetine=75 mg of sertraline=100 venlafaxine;

§ benzodiazepine equivalent dosage, 1 mg of lorazepam=0.5 mg of alprazolam=0.25 mg of clonazepam.

ET, early trauma; PD, panic disorder; HCs, healthy controls; ETISR-SF, Early Trauma Inventory Self-Report Short Form; SSRI, selective serotonin reuptake inhibitor.

Table 2.
Multiple linear regression model for predicting local gyrification index in the gyrus portion of the superior parietal lobule among all participants
Variable (range) R2 ΔR2 ΔF (P) Beta coefficient (B) Standard error B β t p
Model 0.178 0.140 4.725 (<0.001)
Age (18-65) -0.002 0.001 -0.163 -2.156 0.033*
Sex (0-1) -0.073 0.022 -0.245 -3.285 0.001*
Diagnosis (0-1) -0.039 0.040 -0.130 -0.970 0.334
ET exposure (0-27) -0.007 0.003 -0.169 -1.968 0.051
Education year (12-23) -0.015 0.005 -0.251 -2.982 0.003*
SSRI equivalent dosage (0-40) 0.000 0.002 0.008 0.085 0.933
Diagnosis-by-ET exposure interaction (0-27) 0.007 0.003 0.245 2.009 0.046*

Sex (0=male, 1=female), diagnosis (0=healthy controls, 1=PD). SSRI equivalent dosage, 10 mg of escitalopram=12.5 mg of paroxetine=75 mg of sertraline=100 mg of venlafaxine. The “ET exposure” variable is the total ETISR-SF scores used as a continuous variable.

* p<0.05.

ET, early trauma; PD, panic disorder; SSRI, selective serotonin reuptake inhibitors; ETISR-SF, Early Trauma Inventory Self-Report Short Form; R2, coefficient of determination (explained variance); ΔR2, increase of explained variance; ΔF (P), change and significance of F-statistics; β, standardized regression coefficient; t, t-statistics.

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