Abnormal information flow in postpartum depression: A resting-state functional magnetic resonance imaging study

Astrocyte atrophy induced by L-PGDS/PGD2/Src signaling dysfunction in the central amygdala mediates postpartum depression

BACKGROUND

Postpartum depression (PPD) is a serious psychiatric disorder that has significantly adverse impacts on maternal health. Metabolic abnormalities in the brain are associated with numerous neurological disorders, yet the specific metabolic signaling pathways and brain regions involved in PPD remain unelucidated.

METHODS

We performed behavioral test in the virgin and postpartum mice. We used mass spectrometry imaging (MSI) and targeted metabolomics analyses to investigate the metabolic alternation in the brain of GABAAR Delta-subunit-deficient (Gabrd-/-) postpartum mice, a specific preclinical animal model of PPD. Next, we performed mechanism studies including qPCR, Western blot, immunofluorescence staining, electron microscopy and primary astrocyte culture. In the specific knockdown and rescue experiments, we injected the adeno-associated virus into the central amygdala (CeA) of female mice.

RESULTS

We identified that prostaglandin D2 (PGD2) downregulation in the CeA was the most outstanding alternation in PPD, and then validated that lipocalin-type prostaglandin D synthase (L-PGDS)/PGD2 downregulation plays a causal role in depressive behaviors derived from PPD in both wild-type and Gabrd-/- mice. Furthermore, we verified that L-PGDS/PGD2 signaling dysfunction-induced astrocytes atrophy is mediated by Src phosphorylation both in vitro and in vivo.

LIMITATIONS

L-PGDS/PGD2 signaling dysfunction may be only responsible for the depressive behavior rather than maternal behaviors in the PPD, and it remains to be seen whether this mechanism is applicable to all depression types.

CONCLUSION

Our study identified abnormalities in the L-PGDS/PGD2 signaling in the CeA, which inhibited Src phosphorylation and induced astrocyte atrophy, ultimately resulting in the development of PPD in mice.

Bidirectional associations between perinatal allopregnanolone and depression severity with postpartum gray matter volume in adult women

BACKGROUND

Perinatal depression (PND) is a debilitating condition affecting maternal well-being and child development. Allopregnanolone (ALLO) is important to perinatal neuroplasticity, however its relationship with depression severity and postpartum structural brain volume is unknown.

METHOD

We examined perinatal temporal dynamics and bidirectional associations between ALLO and depression severity and the association between these variables and postpartum gray matter volume, using a random intercept cross-lagged panel model.

RESULTS

We identified a unidirectional predictive relationship between PND severity and ALLO concentration, suggesting greater depression severity early in the perinatal period may contribute to subsequent changes in ALLO concentration (β = 0.26, p = 0.009), while variations in ALLO levels during the perinatal period influences the development and severity of depressive symptoms later in the postpartum period (β = 0.38, p = 0.007). Antepartum depression severity (Visit 2, β = 0.35, p = 0.004), ALLO concentration (Visit 2, β = 0.37, p = 0.001), and postpartum depression severity (Visit 3, β = 0.39, p = 0.031), each predicted the right anterior cingulate volume. Antepartum ALLO concentration (Visit 2, β = 0.29, p = 0.001) predicted left suborbital sulcus volume. Antepartum depression severity (Visit 1, β = 0.39, p = 0.006 and Visit 2, β = 0.48, p < 0.001) predicted the right straight gyrus volume. Postpartum depression severity (Visit 3, β = 0.36, p = 0.001) predicted left middle-posterior cingulate volume.

CONCLUSION

These results provide the first evidence of bidirectional associations between perinatal ALLO and depression severity with postpartum gray matter volume.

Neurobiological and Behavioral Underpinnings of Perinatal Mood and Anxiety Disorders (PMADs): A Selective Narrative Review

Perinatal mood and anxiety disorders (PMADs) profoundly impact maternal and infant health, affecting women worldwide during pregnancy and postpartum. This review synthesizes current research on the neurobiological effects of PMADs, particularly their influence on brain structure, function, and corresponding cognitive, behavioral, and mental health outcomes in mothers. A literature search across PubMed, PsycINFO, and Google Scholar yielded studies utilizing neuroimaging (MRI, fMRI) and cognitive assessments to explore brain changes in PMADs. The key findings indicate significant neurobiological alterations in PMADs, such as glutamatergic dysfunction, neuronal damage, and altered neural connectivity, particularly in postpartum depression (PPD). Functional MRI studies reveal distinct patterns of brain function alteration, including amygdala non-responsivity in PPD, differing from traditional major depressive disorder (MDD). These neurobiological changes are connected with cognitive impairments and behavioral modifications, impacting maternal caregiving. Understanding these alterations is fundamental for developing effective treatments. The findings emphasize the importance of focusing on maternal mental health, advocating for early detection, and personalized treatment strategies to improve maternal and child outcomes.

Aberrant structural and functional alterations in postpartum depression: a combined voxel-based morphometry and resting-state functional connectivity study

Objectives

Postpartum depression (PPD) is a severe postpartum psychiatric disorder with unclear pathogenesis. Previous neuroimaging studies have reported structural or functional alterations in areas associated with emotion regulation, cognitive disorder, and parenting behaviors of PPD. The primary goal of this investigation was to explore the presence of brain structural alterations and relevant functional changes in PPD patients.

Methods

A total of 28 patients and 30 matched healthy postnatal women (HPW) underwent both three-dimensional T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. Structural analysis was performed by voxel-based morphometry (VBM), followed by resting-state functional analysis using a seed-based whole-brain functional connectivity (FC) approach with abnormal gray matter volume (GMV) regions as seed.

Results

Compared with HPW, the PPD patients showed increased GMV in the left dorsolateral prefrontal cortex (DLPFC.L), the right precentral gyrus (PrCG.R), and the orbitofrontal cortex (OFC). In the PPD group, the DLPFC.L showed increased FC with the right anterior cingulate and paracingulate gyri (ACG.R) and the right middle frontal gyrus (MFG.R); the FC between the PrCG.R and the right median cingulate and paracingulate gyri (DCG.R) exhibited enhanced; the OFC showed increased FC with MFG.R and the left inferior occipital gyrus (IOG.L). In PPD, GMV of DLPFC.L was positively correlated with EDPS scores (r = 0.409 p = 0.031), and FC of PrCG.R-DCG.R was positively correlated with EDPS scores (r = 0.483 p = 0.020).

Conclusion

Structural and functional damage of the DLPFC.L and OFC is associated with cognitive disorders and parenting behaviors in PPD, while structural abnormalities of the DLPFC.L and PrCG.R are involved in impaired executive function. The increased GMV of DLPFC.L may be a unique structural pathological mechanism of PPD related to the inability of PPD patients to withstand long-term parenting stress. These findings have important implications for understanding neural mechanisms in PPD.

Structural and functional improvement of amygdala sub-regions in postpartum depression after acupuncture

Objective

This study aimed to analyze the changes in structure and function in amygdala sub-regions in patients with postpartum depression (PPD) before and after acupuncture.

Methods

A total of 52 patients with PPD (All-PPD group) were included in this trial, 22 of which completed 8 weeks of acupuncture treatment (Acu-PPD group). An age-matched control group of 24 healthy postpartum women (HPW) from the hospital and community were also included. Results from the 17-Hamilton Depression Scale (17-HAMD) and the Edinburgh Postnatal Depression Scale (EPDS) were evaluated, and resting-state functional magnetic resonance imaging (rs-fMRI) scans were performed at baseline and after the acupuncture treatment. Sub-regions of the amygdala were used as seed regions to measure gray matter volume (GMV) and analyzed for resting-state functional connectivity (RSFC) values separately. Finally, correlation analyses were performed on all patients with PPD to evaluate association values between the clinical scale scores, GMV, and RSFC values, while controlling for age and education. Pearson's correlation analyses were conducted to investigate the relevance between GMV and RSFC values of brain regions that differed before and after acupuncture treatment and clinical scale scores in Acu-PPD patients.

Results

The HAMD scores for Acu-PPD were reduced after acupuncture treatment (P < 0.05), suggesting the positive effects of acupuncture on depression symptoms. Structurally, the All-PPD group showed significantly decreased GMV in the left lateral part of the amygdala (lAMG.L) and the right lateral part of the amygdala (lAMG.R) compared to the HPW group (P < 0.05). In addition, the GMV of lAMG.R was marginally increased in the Acu-PPD group after acupuncture (P < 0.05). Functionally, the Acu-PPD group showed a significantly enhanced RSFC between the left medial part of the amygdala (mAMG.L) and the left vermis_6, an increased RSFC between the right medial part of the amygdala (mAMG.R) and left vermis_6, and an increased RSFC between the lAMG.R and left cerebelum_crus1 (P < 0.05). Moreover, correlation studies revealed that the GMV in the lAMG.R was significantly related to the EPDS scores in the All-PPD group (P < 0.05).

Conclusion

Our findings demonstrated that the structure of amygdala sub-regions is impaired in patients with PPD. Acupuncture may improve depressive symptoms in patients with PPD, and the mechanism may be attributed to changes in the amygdala sub-region structure and the functional connections of brain areas linked to the processing of negative emotions. The fMRI-based technique can provide comprehensive neuroimaging evidence to visualize the central mechanism of action of acupuncture in PPD.

Consistent functional abnormalities in patients with postpartum depression

Postpartum depression (PPD) is a common public health concern. A wide range of functional abnormalities in various brain regions have been reported in fMRI studies on PPD, however, a consistent functional changing pattern is still lacking. Herein, we obtained functional Magnetic Resonance Imaging (fMRI) data from 52 patients with PPD and 24 healthy postpartum women (HPW). Functional indexes (low-frequency fluctuation, degree centrality, and regional homogeneity) were calculated and compared among these groups to explore the functional changing patterns of PPD. Then, correlation analyses were performed to investigate the relationship between changed functional indexes and clinical measurements in the PPD. Finally, support vector machine (SVM) was performed to test whether these abnormal features can be used to distinguish PPD from HPW. As a result, we identified significantly and consistently functional changing pattern characterizing by increased functional activity in the left inferior occipital gyrus and decreased functional activity right anterior cingulate cortex in the PPD as compared to HPW. These functional values in the right anterior cingulate cortex were significantly correlated with depression symptoms in the PPD, and can be used as features to distinguish PPD from HPW. In conclusion, our results suggested that the right anterior cingulate cortex could be served as a functional neuro-imaging biomarker for PPD, which might be used as a potential target for neuro-modulation.

Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression

BACKGROUND

Electroconvulsive therapy is effectively used for treatment-resistant depression; however, its neural mechanism is largely unknown. Resting-state functional magnetic resonance imaging is promising for monitoring outcomes of electroconvulsive therapy for depression. This study aimed to explore the imaging correlates of the electroconvulsive therapy effects on depression using Granger causality analysis and dynamic functional connectivity analyses.

METHODS

We performed advanced analyses of resting-state functional magnetic resonance imaging data at the beginning and intermediate stages and end of the therapeutic course to identify neural markers that reflect or predict the therapeutic effects of electroconvulsive therapy on depression.

RESULTS

We demonstrated that information flow between the functional networks analyzed by Granger causality changes during electroconvulsive therapy, and this change was correlated with the therapeutic outcome. Information flow and the dwell time (an index reflecting the temporal stability of functional connectivity) before electroconvulsive therapy are correlated with depressive symptoms during and after treatment.

LIMITATIONS

First, the sample size was small. A larger group is needed to confirm our findings. Second, the influence of concomitant pharmacotherapy on our results was not fully addressed, although we expected it to be minimal because only minor changes in pharmacotherapy occurred during electroconvulsive therapy. Third, different scanners were used the groups, although the acquisition parameters were the same; a direct comparison between patient and healthy participant data was not possible. Thus, we presented the data of the healthy participants separately from that of the patients as a reference.

CONCLUSIONS

These results show the specific properties of functional brain connectivity.

Classification of major depression disorder via using minimum spanning tree of individual high-order morphological brain network

BACKGROUND

Major depressive disorder (MDD) is an overbroad and heterogeneous diagnosis with no reliable or quantifiable markers. We aim to combine machine-learning techniques with the individual minimum spanning tree of the morphological brain network (MST-MBN) to determine whether the network properties can provide neuroimaging biomarkers to identify patients with MDD.

METHOD

Eight morphometric features of each region of interest (ROI) were extracted from 3D T1 structural images of 106 patients with MDD and 97 healthy controls. Six feature distances of the eight morphometric features were calculated to generate a feature distance matrix, which was defined as low-order MBN. Further linear correlations of feature distances between ROIs were calculated on the basis of low-order MBN to generate individual high-order MBN. The Kruskal's algorithm was used to generate the MST to obtain the core framework of individual low-order and high-order MBN. The regional and global properties of the individual MSTs were defined as the feature. The support vector machine and back-propagation neural network was used to diagnose MDD and assess its severity, respectively.

RESULT

The low-order and high-order MST-MBN constructed by cityblock distance had the excellent classification performance. The high-order MST-MBN significantly improved almost 20 % diagnostic accuracy compared with the low-order MST-MBN, and had a maximum R² value of 0.939 between the predictive and true Hamilton Depression Scale score. The different group-level connectivity strength mainly involves the central executive network and default mode network (no statistical significance after FDR correction).

CONCLUSION

We proposed an innovative individual high-order MST-MBN to capture the cortical high-order morphological correlation and make an excellent performance for individualized diagnosis and assessment of MDD.

Structural, functional, and metabolic signatures of postpartum depression: A systematic review

OBJECTIVE

Postpartum depression (PPD) is a serious condition with debilitating consequences for the mother, offspring, and the whole family. The scope of negative outcomes of PPD highlights the need to specify effective diagnostics and treatment which might differ from major depressive disorder (MDD). In order to improve our clinical care, we need to better understand the underlying neuropathological mechanisms of PPD. Therefore, we conducted a systematic review of published neuroimaging studies assessing functional, structural, and metabolic correlates of PPD.

METHODS

Relevant papers were identified using a search code for English-written studies in the PubMed, Scopus, and Web of Science databases published by March 2022. Included were studies with structural magnetic resonance imaging, functional magnetic resonance imaging, both resting-state and task-related, magnetic resonance spectroscopy, or positron emission tomography. The findings were analyzed to assess signatures in PPD-diagnosed women compared to healthy controls. The review protocol was registered in PROSPERO (CRD42022313794).

RESULTS

The total of 3,368 references were initially identified. After the removal of duplicates and non-applicable papers, the search yielded 74 full-text studies assessed for eligibility. Of them, 26 met the inclusion criteria and their findings were analyzed and synthesized. The results showed consistent functional, structural, and metabolic changes in the default mode network and the salient network in women with PPD. During emotion-related tasks, PPD was associated with changes in the corticolimbic system activity, especially the amygdala.

DISCUSSION

This review offers a comprehensive summary of neuroimaging signatures in PPD-diagnosed women. It indicates the brain regions and networks which show functional, structural, and metabolic changes. Our findings offer better understanding of the nature of PPD, which clearly copies some features of MDD, while differs in others.

Improved Interhemispheric Functional Connectivity in Postpartum Depression Disorder: Associations With Individual Target-Transcranial Magnetic Stimulation Treatment Effects

Postpartum depression (PPD) is a depressive condition that is associated with a high risk of stressful life events, poor marital relationships, and even suicide. Neuroimaging techniques have enriched our understanding of cerebral mechanisms underlying PPD; namely, abnormalities in the amygdala-insula-frontal circuit might contribute to the pathogenesis of PPD. Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT) is a recently validated neuroscience-informed accelerated intermittent theta-burst stimulation repetitive transcranial magnetic stimulation (rTMS) protocol. It has been shown to be effective, safe, tolerable, and rapid acting for treating treatment-resistant depression, and may be a valuable tool in the treatment of PPD. The purpose of the current study was to detect inter-hemispheric connectivity changes and their relationship with the clinical treatment effects of rTMS. Resting-state fMRI data from 32 patients with PPD treated with SAINT were collected and compared with findings from 32 age matched healthy controls. Voxel-mirrored homotopic connectivity (VMHC) was used to analyze the patterns of interhemispheric intrinsic functional connectivity in patients with PPD. Scores on the 17-item Hamilton Depression Rating Scale, Edinburgh Postnatal Depression Scale (EPDS) scores, and the relationships between these clinical characteristics and VMHC were the primary outcomes. Patients with PPD at baseline showed reduced VMHC in the amygdala, insula, and medial frontal gyrus compared with the HCs. These properties showed a renormalization after individualized rTMS treatment. Furthermore, increased connectivity between the left and right insula after SAINT was significantly correlated with the improvement of EPDS scores. Our results reveal the disruptions in the intrinsic functional architecture of interhemispheric communication in patients with PPD, and provide evidence for the pathophysiological mechanisms and the effects of rTMS.

Information Flow Pattern in Early Mild Cognitive Impairment Patients

Purpose: To investigate the brain information flow pattern in patients with early mild cognitive impairment (EMCI) and explore its potential ability of differentiation and prediction for EMCI.

Methods: In this study, 49 patients with EMCI and 40 age- and sex-matched healthy controls (HCs) with available resting-state functional MRI images and neurological measures [including the neuropsychological evaluation and cerebrospinal fluid (CSF) biomarkers] were included from the Alzheimer's Disease Neuroimaging Initiative. Functional MRI measures including preferred information flow direction between brain regions and preferred information flow index of each brain region parcellated by the Atlas of Intrinsic Connectivity of Homotopic Areas (AICHA) were calculated by using non-parametric multiplicative regression-Granger causality analysis (NPMR-GCA). Edge- and node-wise Student's t-test was conducted for between-group comparison. Support vector classification was performed to differentiate EMCI from HC. The least absolute shrinkage and selection operator (lasso) regression were used to evaluate the predictive ability of information flow measures for the neurological state.

Results: Compared to HC, disturbed preferred information flow directions between brain regions involving default mode network (DMN), executive control network (ECN), somatomotor network (SMN), and visual network (VN) were observed in patients with EMCI. An altered preferred information flow index in several brain regions (including the thalamus, posterior cingulate, and precentral gyrus) was also observed. Classification accuracy of 80% for differentiating patients with EMCI from HC was achieved by using the preferred information flow directions. The preferred information flow directions have a good ability to predict memory and executive function, level of amyloid β, tau protein, and phosphorylated tau protein with the high Pearson's correlation coefficients (r > 0.7) between predictive and actual neurological measures.

Conclusion: Patients with EMCI were presented with a disturbed brain information flow pattern, which could help clinicians to identify patients with EMCI and assess their neurological state.

Characterizing the Brain Structural Adaptations Across the Motherhood Transition

Women that become mothers face notable physiological adaptations during this life-period. Neuroimaging studies of the last decade have provided grounded evidence that women's brains structurally change across the transition into motherhood. The characterization of this brain remodeling is currently in its early years of research. The current article reviews this scientific field by focusing on our longitudinal (pre-to-post pregnancy) Magnetic Resonance Imaging (MRI) studies in first-time parents and other longitudinal and cross-sectional studies of parents. We present the questions that are currently being answered by the parental brain literature and point out those that have not yet been explored. We also highlight potential confounding variables that need to be considered when analyzing and interpreting brain changes observed during motherhood.

Altered gray matter structural covariance networks in postpartum depression: a graph theoretical analysis

BACKGROUND

Postpartum depression (PPD) is a serious postpartum mental health problem worldwide. To date, minimal is known about the alteration of topographical organization in the brain structural covariance network of patients with PPD. This study investigates the brain structural covariance networks of patients with PPD by using graph theoretical analysis.

METHODS

High-resolution 3D T1 structural images were acquired from 21 drug-naive patients with PPD and 18 healthy postpartum women. Cortical thickness was extracted from 64 brain regions to construct the whole-brain structural covariance networks by calculating the Pearson correlation coefficients, and their topological properties (e.g., small-worldness, efficiency, and nodal centrality) were analyzed by using graph theory. Nonparametric permutation tests were further used for group comparisons of topological metrics. A node was set as a hub if its betweenness centrality (BC) was at least two standard deviations higher than the mean nodal centrality. Network-based statistic (NBS) was used to determine the connected subnetwork.

RESULTS

The PPD and control groups showed small-worldness of group networks, but the small-world network was more evidently in the PPD group. Moreover, the PPD group showed increased network local efficiency and almost similar network global efficiency. However, the difference of the network metrics was not significant across the range of network densities. The hub nodes of the patients with PPD were right inferior parietal lobule (BC = 13.69) and right supramarginal gyrus (BC = 13.15), whereas those for the HCs were left cuneus (BC = 14.96), right caudal anterior-cingulate cortex (BC = 15.51), and right precuneus gyrus (BC = 15.74). NBS demonstrated two disrupted subnetworks that are present in PPD: the first subnetwork with decreased internodal connections is mainly involved in the cognitive-control network and visual network, and the second subnetwork with increased internodal connections is mainly involved in the default mode network, cognitive-control network and visual network.

CONCLUSIONS

This study demonstrates the alteration of topographical organization in the brain structural covariance network of patients with PPD, providing in sight on the notion that PPD could be characterized as a systems-level disorder.

Altered amygdala effective connectivity in migraine without aura: evidence from resting-state fMRI with Granger causality analysis

BACKGROUND

Granger causality analysis (GCA) has been used to investigate the pathophysiology of migraine. Amygdala plays a key role in pain modulation of migraine attack. However, the detailed neuromechanism remained to be elucidated. We applied GCA to explore the amygdala-based directional effective connectivity in migraine without aura (MwoA) and to determine the relation with clinical characteristics.

METHODS

Forty-five MwoA patients and forty age-, sex-, and years of education-matched healthy controls(HCs) underwent resting-state functional magnetic resonance imaging (fMRI). Bilateral amygdala were used as seed regions in GCA to investigate directional effective connectivity and relation with migraine duration or attack frequency.

RESULTS

MwoA patients showed significantly decreased effective connectivity from right amygdala to right superior temporal gyrus, left superior temporal gyrus and right precentral gyrus compared with HCs. Furthermore, MwoA patients demonstrated significantly decreased effective connectivity from the left amygdala to the ipsilateral superior temporal gyrus. Also, MwoA patients showed enhanced effective connectivity from left inferior frontal gyrus to left amygdala. Effective connectivity outflow from right amygdala to right precentral gyrus was negatively correlated to disease duration.

CONCLUSIONS

Altered directional effective connectivity of amygdala demonstrated that neurolimbic pain networks contribute to multisensory integration abnormalities and deficits in pain modulation of MwoA patients.