Differential grey matter structure in women with premenstrual dysphoric disorder: evidence from brain morphometry and data-driven classification

Abstract

Abstract Premenstrual dysphoric disorder (PMDD) is a female-specific condition classified in the Diagnostic and Statical Manual—5th edition under depressive disorders. Alterations in grey matter volume, cortical thickness and folding metrics have been associated with a number of mood disorders, though little is known regarding brain morphological alterations in PMDD. Here, women with PMDD and healthy controls underwent magnetic resonance imaging (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. Machine learning and multivariate pattern analysis were performed to test whether MRI data could distinguish women with PMDD from healthy controls. Compared to controls, women with PMDD had smaller grey matter volume in ventral posterior cortices and the cerebellum (Cohen’s d = 0.45–0.76). Region-of-interest analyses further indicated smaller volume in the right amygdala and putamen of women with PMDD (Cohen’s d = 0.34–0.55). Likewise, thinner cortex was observed in women with PMDD compared to controls, particularly in the left hemisphere (Cohen’s d = 0.20–0.74). Classification analyses showed that women with PMDD can be distinguished from controls based on grey matter morphology, with an accuracy up to 74%. In line with the hypothesis of an impaired top-down inhibitory circuit involving limbic structures in PMDD, the present findings point to PMDD-specific grey matter anatomy in regions of corticolimbic networks. Furthermore, the results include widespread cortical and cerebellar regions, suggesting the involvement of distinct networks in PMDD pathophysiology.