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Grey matter morphometry and MRI data-driven classification of premenstrual dysphoric disorder
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- Dubol, Manon (author)
- Uppsala universitet,Institutionen för kvinnors och barns hälsa,Neuropsychopharmacology - Comasco group
- Stiernman, Louise (author)
- Sundström-Poromaa, Inger (author)
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- Bixo, Marie (author)
- Comasco, Erika (author)
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- (creator_code:org_t)
- Glasgow, Scotland, 2022
- 2022
- English.
- Conference paper (other academic/artistic)
Abstract
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- Introduction. Premenstrual dysphoric disorder (PMDD) is recognized in the DSM-5 as a hormone-related depressive disorder, specific to women’s mental health 1. Women who suffer from PMDD experience affective, cognitive, and physical symptoms that peak during the late luteal phase of the menstrual cycle, and remit shortly in the beginning of the next cycle 2. The key affective symptoms of PMDD point to anatomical and functional brain impairment, suggesting an impaired top-down inhibitory process involving limbic brain structures 3. However, very little is known about brain morphological alterations in PMDD. The present study aimed at investigating the grey matter structures that distinguish women with PMDD from healthy controls, by use of multiscale structural MRI analyses. Differences in grey matter morphology between women with PMDD and healthy controls were expected within regions of cortico-limbic networks. Methods. Women meeting DSM-5 criteria for PMDD (N=89) and healthy controls (N=42) underwent structural 3T-MRI during the luteal phase of the menstrual cycle. Differences in grey matter structure between the groups were investigated by use of Voxel- and Surface Based Morphometry in SPM12, using whole-brain and region-of-interest approaches. Voxel- and vertex-wise analyses were conducted using the non-parametric permutation-based threshold-free cluster enhancement method 4. In order to account for the nuisance variance of regressors of non-interest, total intracranial volume and age were included as confounding covariates. Furthermore, machine learning and multivariate pattern analysis was performed using a leave-one-fold-out cross-validation procedure with the MVPANI toolbox 5, to test whether MRI measures (volume, thickness, gyrification, sulcal depth and cortical complexity) could distinguish women with PMDD from healthy controls.Results. Compared to controls over the whole brain, women with PMDD had smaller grey matter volumes in ventral posterior cortices (fusiform, lingual, inferior occipital and parahippocampal cortices) and the cerebellum (Cohen’s d = 0.45 ― 0.76). Region-of-interest analyses further indicated smaller volumes in the right amygdala and putamen of women with PMDD (Cohen’s d = 0.34 ― 0.55). Likewise, women with PMDD displayed thinner cortices compared to controls, in widespread clusters covering frontal, temporal, insular, paracentral, parietal, and occipital areas (Cohen’s d = 0.20 ― 0.74). No differences in gyrification, sulcal depth and cortical complexity were found between women with PMDD and controls. Classification analyses showed that women with PMDD can be distinguished from controls based on grey matter morphology, above chance level. Notably, grey matter volume was the best measure for distinguishing the groups, with a mean accuracy of about 73%.Conclusions. The present findings point to PMDD-specific grey matter structure in regions of corticolimbic networks, in line with the hypothesis of an impaired top-down inhibitory circuit involving limbic structures in PMDD. Furthermore, the results include widespread cortical regions and cerebellar areas, suggesting the involvement of distinct networks in PMDD pathophysiology. These effects prominently involved volumetric and cortical thickness measures, as further highlighted by multivariate pattern classification analyses. Such differences in brain structure may help explaining the variations in brain function previously reported in women with PMDD during the symptomatic phase.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Neurosciences (hsv//eng)
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