Harmonizing Depression Scales with Item Response Theory: Brain Structure Associations in BD and MDD
Poster No:
406
Submission Type:
Abstract Submission
Authors:
Emma Corley1, John O'Connor1, Brian Hallahan1, Genevieve McPhilemy1, Leila Nabulsi2, Melody Kang2, Elena Pozzi3, Dick Veltman4, Lianne Schmaal3, Sophia Thomopoulos2, Paul Thompson2, Ole Andreasson5, Chris Ching2, Colm McDonald1, Dara Cannon1
Institutions:
1University of Galway, Ireland, 2University of Southern California, Los Angeles, CA, 3The University of Melbourne, Parkville, Victoria, 4Amsterdam UMC, Netherlands, 5Oslo University Hospital, Norway
First Author:
Co-Author(s):
Introduction:
Structural brain abnormalities are frequently observed in major depressive disorder (MDD) and bipolar disorder (BD). However, prior studies have encountered challenges linking these alterations to specific symptoms, partly due to challenges in aggregating and replicating symptom data across multi-site studies. Diverse mood rating scales further complicate this process, as traditional approaches sum item scores, assuming equal contribution from each item, which can undermine the reliability and validity of depression phenotyping.To address these limitations, we used Item Response Theory(IRT) to harmonise multiple depression scales providing enhanced measurement precision and facilitating more robust investigations of brain-symptom associations.
Methods:
Data from 10,269 participants(6,090 CN, 3,104 BD, 1,075 MDD) across 50 sites in the ENIGMA MDD and BD groups were included. Subcortical volumes were derived via FreeSurfer from 3D T1-weighted brain MRI scans. Site effects were harmonized using ComBat(Radua, 2024). For IRT, a graded response model was implemented(mirt R). Calibration was conducted on a subset of 586 participants with complete data across four measures of depression. Harmonization followed a stepwise approach: first among those with data for all four scales, then for those with at least two scales, and finally for those with data from a single scale. Exploratory factor analysis identified five symptom clusters: cognitive/affective symptoms, suicidal ideation, anxiety, motivational deficits, and somatic symptoms. An overall IRT model was applied across scales to harmonize symptom severity, followed by IRT modelling within each symptom cluster. Regression models examined group differences in subcortical volumes(BD, MDD, CN) and symptom severity, controlling for age, sex and ICV, and FDR corrected.
·Association between IRT depression latent scores and subcortical volume in the total sample (N= 10,269)
Results:
BD showed the largest volumetric reductions compared to MDD in the pallidum(β=-0.162, p=4.7×10⁻⁷), amygdala(β =-0.145, p=7.25×10⁻⁶), and accumbens (β =-0.126, p=1.23×10⁻⁴). Higher IRT-derived depression scores were significantly associated with smaller hippocampal, putamen, and pallidum volumes(βrange=-0.146 to -0.032, pFDR <0.05, Fig 1).These associations were stronger than those observed with traditional depression scales(Fig 2). Specific symptom clusters showed distinct associations: suicidal ideation was linked to thalamic and hippocampal volumes(β=-0.207 to -0.134), and anxiety symptoms were associated with the thalamus, putamen, pallidum, hippocampus and accumbens volumes. Diagnosis by symptom cluster interactions revealed that BD participants exhibited stronger associations between suicidal ideation and caudate volume, as well as between cognitive/affective symptoms and amygdala volume. In contrast, MDD participants demonstrated significant associations between cognitive/affective symptoms and hippocampal volume.
·Correlation of IRT scores and traditional sum score measures of depression and subcortical volume
Conclusions:
In the largest neuroimaging sample with clinical data, we observed significant differences in subcortical volumes in BD and MDD. IRT scores showed stronger associations with hippocampal, putamen and pallidum volumes, suggesting enhanced sensitivity compared to traditional sum-scores. Disorder-specific symptom interactions were identified: in BD, suicidal ideation was linked to the caudate, and cognitive/affective symptoms to the amygdala, while in MDD, cognitive/affective symptoms were associated with the hippocampus. Our findings align with prior research, such as hippocampal reductions in MDD (Schmaal et al., 2016) and altered caudate volume in suicide attempters (Ho et al., 2021), but differ by incorporating cross disorder comparisons with item-level data, providing new insights into regional-symptom patterns. While both disorders shared overlapping regions, these results highlight distinct neurobiological mechanisms, such as potential reward system dysfunction in BD. Overall, our findings emphasize the utility of IRT in enhancing phenotyping precision and advancing multi-site neuroimaging studies in mood disorders.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Multivariate Approaches
Other Methods
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures 2
Keywords:
Affective Disorders
Data analysis
DISORDERS
Psychiatric Disorders
Statistical Methods
STRUCTURAL MRI
Sub-Cortical
Other - Harmonisation
1|2Indicates the priority used for review
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Schmaal, L., Veltman, D. J., van Erp, T. G., Sämann, P. G., Frodl, T., Jahanshad, N., ... & Hibar, D. P. (2016). Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Molecular psychiatry, 21(6), 806-812.