Social support mediates the influence of cerebellum functional connectivity strength on postpartum depression and postpartum depression with anxiety

Abstract

Post-Partum Depression (PPD) is the most common health issue impacting emotional well being in women and is often comorbid with anxiety (PPD-A). Previous studies have shown that adequate social support can protect against PPD and PPD-A. However, how the brain connectome is disrupted in PPD and PPD-A and the neural basis underlying the role of social support in PPD and PPD-A remains unclear. The present study aims to explore these issues in patients with PPD and PPD-A. Well-established questionnaires and resting-state functional Magnetic Resonance Imaging (rsfMRI) were performed in 45 PPD, 31 PDD-A patients and 62 Healthy Postnatal Women (HPW). Brain functional integration was measured by analysis of Functional Connectivity Strength (FCS). Association and mediation analyses were performed to investigate relationships between FCS, PPD and PPD-A symptoms and social support. PPD patients showed specifically higher FCS in right parahippocampus, whereas PPD-A patients showed specifically higher FCS in left ventrolateral prefrontal cortex. In all postpartum women, depression symptoms positively correlated with FCS in left paracentral lobule; depression and anxiety symptoms were negatively correlated with FCS in right cerebellem posterior lobe (CPL), a brain region implicated in supporting social cognition and regulation of emotion. Subsequent mediation analysis revealed that perceived social support mediated the association between right CPL FCS and PPD and PPD-A symptoms. Measurement of FCS in disorder-specific neural circuits offers a potential biomarker to study and measure the efficacy of social support for PPD and PPD-A.

Altered Long- and Short-Range Functional Connectivity Density in Patients With Thyroid-Associated Ophthalmopathy: A Resting-State fMRI Study

“…PCL has bidirectional connections with precuneus ( 44 ), which is an important component of default mode network associated with mood disorder ( 45 ). Lots of research have shown structural and functional alterations in the PCL of depression and depression-related disorders ( 46 , 47 ). Therefore, combing the elevated HARS and HDRS scores in the patient group, the reduction of local functional connectivity in SMA and PCL may also be associated with the emotional disturbance in patients with TAO.…”

Abnormal Voxel-Based Degree Centrality in Patients With Postpartum Depression: A Resting-State Functional Magnetic Resonance Imaging Study

“…Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to detect spontaneous neural brain activity in PPD using the amplitude of low-frequency fluctuation (ALFF) analysis ( Deligiannidis et al, 2013 , 2019 ; Chase et al, 2014 ) or dynamic ALFF ( Cheng et al, 2022b ), regional homogeneity (ReHo) analysis ( Xiao-juan et al, 2011 ), voxel-mirrored homotopic connectivity ( Zhang et al, 2020 ), dynamic or static functional connectivity (FC) ( Cheng et al, 2022b ), functional connectivity density (FCD) ( Cheng et al, 2021 ), and functional connectivity strength (FCS) ( Cheng et al, 2022a ). Compared with healthy controls (HCs), mothers with PPD showed significantly increased ReHo in the posterior cingulate and medial frontal gyrus and decreased ReHo in the temporal gyrus ( Xiao-juan et al, 2011 ).…”

“…Moreover, the altered FCD and resting-state FC were closely associated with depression and anxiety symptoms load ( Cheng et al, 2021 ). The PPD group showed specifically higher FCS in right parahippocampus, and perceived social support mediated the influence of FCS in the right cerebellum posterior lobe on depression and anxiety symptoms ( Cheng et al, 2022a ). These studies can help clarify how PPD may affect a mother’s baseline brain activity at rest and provide a more comprehensive understanding of neural circuitry dysfunction in mothers with PPD.…”

Prediction of childhood maltreatment and subtypes with personalized functional connectome of large‐scale brain networks

“…To determine the contribution of each network during prediction, the identified networks through NMF method were classified into eight networks including seven cortical networks (visual network (VS), motor network (Dauvermann et al, 2021), limbic network (LMB, Cheng, Roberts, et al, 2022), default mode network (Dannlowski et al, 2012), ventral attention network (Cui et al, 2020), dordal attention network (Tomoda et al, 2009), frontoparietal network (FPN), and a cerebellum network in according to the Yeo group atlas (Yeo et al, 2011). Feature weights of each FNC were assigned to the corresponding connected networks, and the positive weights which made contribution for prediction were included.…”