Cortical morphology variations during the menstrual cycle in individuals with and without premenstrual dysphoric disorder.

BACKGROUND: Premenstrual dysphoric disorder (PMDD) is hypothesized to stem from maladaptive neural sensitivity to ovarian steroid hormone fluctuations. Recently, we found thinner cortices in individuals with PMDD, compared to healthy controls, during the symptomatic phase. Here, we aimed at investigating whether such differences illustrate state-like characteristics specific to the symptomatic phase, or trait-like features defining PMDD. METHODS: Patients and controls were scanned using structural magnetic resonance imaging during the mid-follicular and late-luteal phase of the menstrual cycle. Group-by-phase interaction effects on cortical architecture metrics (cortical thickness, gyrification index, cortical complexity, and sulcal depth) were assessed using surface-based morphometry. RESULTS: Independently of menstrual cycle phase, a main effect of diagnostic group on surface metrics was found, primarily illustrating thinner cortices (0.3 < Cohen's d > 1.1) and lower gyrification indices (0.4 < Cohen's d > 1.0) in patients compared to controls. Furthermore, menstrual cycle-specific effects were detected across all participants, depicting a decrease in cortical thickness (0.4 < Cohen's d > 1.7) and region-dependent changes in cortical folding metrics (0.4 < Cohen's d > 2.2) from the mid-follicular to the late luteal phase. LIMITATIONS: Small effects (d = 0.3) require a larger sample size to be accurately characterized. CONCLUSIONS: These findings provide initial evidence of trait-like cortical characteristics of the brain of individuals with premenstrual dysphoric disorder, together with indications of menstrual cycle-related variations in cortical architecture in patients and controls. Further investigations exploring whether these differences constitute stable vulnerability markers or develop over the years may help understand PMDD etiology.

Emotion-induced brain activation across the menstrual cycle in individuals with premenstrual dysphoric disorder and associations to serum levels of progesterone-derived neurosteroids.

Premenstrual dysphoric disorder (PMDD) is a debilitating disorder characterized by severe mood symptoms in the luteal phase of the menstrual cycle. PMDD symptoms are hypothesized to be linked to an altered sensitivity to normal luteal phase levels of allopregnanolone (ALLO), a GABAA-modulating progesterone metabolite. Moreover, the endogenous 3ß-epimer of ALLO, isoallopregnanolone (ISO), has been shown to alleviate PMDD symptoms through its selective and dose-dependent antagonism of the ALLO effect. There is preliminary evidence showing altered recruitment of brain regions during emotion processing in PMDD, but whether this is associated to serum levels of ALLO, ISO or their relative concentration is unknown. In the present study, subjects with PMDD and asymptomatic controls underwent functional magnetic resonance imaging (fMRI) in the mid-follicular and the late-luteal phase of the menstrual cycle. Brain responses to emotional stimuli were investigated and related to serum levels of ovarian steroids, the neurosteroids ALLO, ISO, and their ratio ISO/ALLO. Participants with PMDD exhibited greater activity in brain regions which are part of emotion-processing networks during the late-luteal phase of the menstrual cycle. Furthermore, activity in key regions of emotion processing networks - the parahippocampal gyrus and amygdala - was differentially associated to the ratio of ISO/ALLO levels in PMDD subjects and controls. Specifically, a positive relationship between ISO/ALLO levels and brain activity was found in PMDD subjects, while the opposite was observed in controls. In conclusion, individuals with PMDD show altered emotion-induced brain responses in the late-luteal phase of the menstrual cycle which may be related to an abnormal response to physiological levels of GABAA-active neurosteroids.

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

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.

White matter microstructure and volume correlates of premenstrual dysphoric disorder.

BACKGROUND: Premenstrual dysphoric disorder (PMDD) is a mood disorder characterized by psychological and physical symptoms. Differences in white matter have been associated with affective and anxiety disorders, which share some symptoms with PMDD. However, whether white matter structure differs between the brains of individuals with PMDD and healthy controls is not known, nor is its relation to symptom severity. METHODS: We performed tract-based spatial statistics and voxel-based morphometry analyses of diffusion tensor imaging metrics and white matter volume, using 2 neuroimaging data sets (n = 67 and n = 131) and a combined whole-brain and region-of-interest approach. We performed correlation analyses to investigate the relationship between regions with different white matter microstructure and volume and PMDD symptom severity. RESULTS: We found greater fractional anisotropy in the left uncinate fasciculus (d = 0.69) in individuals with PMDD compared to controls. Moreover, the volume of the right uncinate fasciculus was higher in individuals with PMDD compared to controls (d = 0.40). As well, the severity of premenstrual depression was positively correlated with fractional anisotropy in the right superior longitudinal fasciculus (r = 0.35). LIMITATIONS: It is challenging to interpret group differences in diffusion tensor imaging metrics in terms of their underlying biophysical properties. The small size of the control group in the diffusion tensor imaging study may have prevented effects of interest from being detected. CONCLUSION: The findings of the present study provide evidence of differential cerebral white matter structure associated with PMDD and its symptoms.