The dynamic functional connectivity of the left rostral hippocampus involved in mediating the association between hippocampal volume and antidepressant efficacy in major depressive disorder

doi:10.21203/rs.3.rs-2958412/v1

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The dynamic functional connectivity of the left rostral hippocampus involved in mediating the association between hippocampal volume and antidepressant efficacy in major depressive disorder

https://doi.org/10.21203/rs.3.rs-2958412/v1

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The hippocampus is highly involved in the pathophysiology of major depressive disorder (MDD), indicating some changes in hippocampal structure and function during MDD condition and also due to antidepressant treatment. However, it is unclear whether structure factors of the hippocampus can effectively impact antidepressant responses by hippocampal functional activity in MDD patients. The longitudinal data were collected from 36 MDD patients before and after 3 months of antidepressant pharmacotherapy. Baseline data from 43 sex- and age-matched healthy controls were also acquired. The dynamic functional connectivity (dFC) of the hippocampal subregions was estimated via a sliding-window method based on resting-state functional magnetic resonance imaging (rs-fMRI). The voxel-based morphometry (VBM) was used to calculate the gray matter volume. The results indicated that patients with MDD exhibited significantly lower dFC of the left rostral hippocampus (rHipp.L) with the right precentral gyrus, left superior temporal gyrus and left postcentral gyrus when compared to healthy controls at baseline. In MDD patients, the dFC of the rHipp.L with right precentral gyrus at baseline was correlated with both the rHipp.L volume and HAMD remission rate (RR%), and also mediated the effects of the rHipp.L volume on antidepressant performance. Our findings suggested that hippocampal functional activity in MDD might continue to act on its structure and further affect antidepressant performance, which provided a novel insight into the neurobiological mechanism of the development route of the therapeutic process for MDD.

Major depressive disorder

Mediating effect

Dynamic functional connectivity

Hippocampal volume

HAMD remission rate

Major depressive disorder (MDD) is a common but very serious debilitating disease which is usually characterized by depressed mood or loss of interest along with other symptoms, including significant changes in weight or appetite, hypersomnia or insomnia, retardation or psychomotor agitation nearly every day, and feelings of worthlessness or excessive or inappropriate guilt, that last for at least 2 weeks and affect people’s normal function (Roehr, 2013). The nature of the clinical disturbance may give clues to the neuropathology of MDD, typified by a wide-ranging distribution of brain alterations involved in cognitive dysfunction, emotion processing and physical symptoms (Hamann, 2012). MDD has been ranked as the main cause of the burden of disease worldwide by WHO (Xiao et al., 2021). Furthermore, the prevalence of MDD is extraordinarily high and growing over time.

Although antidepressant medication (ADM) has been recommended as the first-line treatment for MDD patients, even after standard antidepressant treatment, the treatment remission rate is only 30%-40% (Rush et al., 2006). In most circumstances, clinicians need several weeks to examine the treatment response and determine whether to change the medical treatment plan in clinical practice, which would prolong the suffering of MDD patients (Bauer et al., 2015; Qaseem et al., 2016). The treatment of MDD can be characterized by 3 phases: acute phase (0 to 3 months), continuation phase (4 to 9 months), and maintenance phase (≥ 1 year) (Sobieraj et al., 2019). Clinically, psychiatrists strive to control MDD patients' depressive symptoms within 3 months to achieve clinical cure as much as possible and promote the recovery of function to the pre-disease level. The outcome and prognosis of the disease depend on the curative in the acute phase, and 3-month is the critical time point for treatment. Therefore, exploring and predicting the improvement after 3 months of treatment will help psychiatrists select suitable treatment schemes for the continuation phase and the maintenance phase. It will also improve the treatment remission rate of patients with MDD. A previous meta-analysis based on studies over the past 15 years has revealed that different domains of biomarkers have already been tested for their capacity to predict response to antidepressant treatment. Compared to cognition, proteins, electrophysiology or genetics, imaging biomarkers showed a more desirable predictive manner, and it can help clinicians flexibly employ alternative treatment procedures or combination therapies on those patients who are insensitive to first-line antidepressants (Voegeli et al., 2017).

Resting-state functional magnetic resonance imaging (rs-fMRI) has provided an effective method to study intrinsic spontaneous brain activity without external task demands. The hippocampus is a pivotal brain region that participates in a series of cognitive and affective functions (Barkus et al., 2010; Strange et al., 2014), previous research (Boku et al., 2018; Sheline et al., 1996) has discussed that long-term exposure to high levels of glucocorticoids can increase neuronal cell death in the hippocampus and cause the hippocampus to shrink and lead to impairments in hippocampal synaptic plasticity in MDD patients, eventually resulting cognitive impairments related to the pathology of the hippocampus (Sapolsky et al., 1986). Several magnetic resonance imaging (MRI) research has revealed that a smaller hippocampal volume and anomalous hippocampal functional connectivity (FC) might cause damage in emotion regulation and memory (Cao et al., 2012; Kaiser et al., 2015; Santos et al., 2018), especially those memories related to negative emotions in MDD patients (LaBar & Cabeza, 2006; Zeng et al., 2012). These findings indicated that the abnormal structure and function of the hippocampus might be core components of the physiopathology of MDD. In the research of the antidepressant treatment of MDD patients with the hippocampus as a neuroimaging biomarker, a study demonstrated that a ‘less abnormal’ hippocampal volume can predict a quicker response to antidepressants and a better treatment remission (Hu et al., 2018). In animal research, even after short-term treatment, antidepressant treatment has been revealed to reverse impaired neurogenesis and neuroplasticity in the hippocampus (Hajszan et al., 2005; Serafini, 2012). However, because antidepressants can significantly increase hippocampal volume and the effects might persist even after a washout period (Hu et al., 2018), as well as the complex relationship between hippocampal volume alteration and illness duration, it is complicated and difficult to only use hippocampal volume to predict the antidepressant efficacy. Increasing studies have shown that the aberrant hippocampal FC has the ability to predict a poor antidepressant response after the acute phase treatment. One recent research reported the predictive value of hippocampal FC for the antidepressant treatment response after 2-week treatment (Xiao et al., 2021), and another study indicated that the hippocampal functional connectivity patterns of brain regions between and within networks might play a pivotal role in identifying a favorable response for the 8 weeks’ treatment for patients with MDD (Chin Fatt et al., 2019). Therefore, it is more reliable to use FC and volume together to predict medical efficacy.

However, previous studies mainly used static functional connectivity (Peng et al., 2018; Y. Wang et al., 2020). Using this approach, an implicit assumption is that FC remains throughout the entire duration of the MRI scan. These time-averaged FC metrics would ignore the dynamic characteristic of MRI signals and the underlying temporal variations of FC which may supply additional information about brain activity (Zhang et al., 2018). This temporal fluctuation of FC is referred to as dynamic functional connectivity (dFC). By using techniques of dynamic analysis, we can track the real-time activity changes in brain connectivity across different brain states. Recent evidence has demonstrated that dynamic functional connectivity can provide new information on temporal variability of rsFC and also recurring patterns of rsFC over time (He et al., 2018; Tu et al., 2020). Currently, in the fields of neuroscience and mental illness, more and more studies applied dFC to depict the brain alterations in some neuropsychiatric diseases including attention deficit hyperactivity disorder, schizophrenia, especially major depressive disorder (Shunkai et al., 2021; Zhou et al., 2021). Meanwhile, the structural complexity and functional diversity of the hippocampus demonstrate the existence of different structural and functional subdivisions within this structure (Poppenk et al., 2013; Strange et al., 2014). Many studies have showed that separate hippocampal subregions have different effects on different emotional and cognitive activities (Dalton & Maguire, 2017; Fanselow & Dong, 2010; Small et al., 2011). One recent research illustrated that using specific subfields of the hippocampus as neuroimaging biomarkers may improve the ability to choose the best first-time treatment strategy for newly diagnosed patients with MDD (Hu et al., 2018). Therefore, we conjectured that, compared to using the unsubdivided whole hippocampus, employing specific hippocampal subfield might have better predictive value for antidepressant efficacy in patients with MDD.

In the present research, we were to characterize the relationships among the volume of specific hippocampal subregions, the dynamic functional connectivity and 3-month antidepressant pharmacotherapy outcomes for MDD patients. We hypothesized that the dFC of the hippocampal subregion would be associated with both the hippocampal volume and the antidepressant efficacy, and would mediate the relationship between them. The primary goal was to search for novel evidence for the application of neuroimaging techniques in the prediction of treatment efficacy and to enrich more individualized therapy proposal for MDD patients.

2.1 Participants

The demographic and clinical characteristics of the participants were summarized in Table 1. Thirty-six MDD patients (age: 28.03 ± 10.20 years; gender: 10 females / 26 males) and forty-three healthy controls (age: 29.42 ± 12.56 years; gender: 27 females / 16 males) were included in the present study. The interviews and diagnoses of MDD patients were completed by certified psychiatrists from the Affiliated Mental Health Center of Zhejiang University School of Medicine by the Mini Neuropsychiatric International Interview (MINI) following the criteria of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). The severity of depressive symptoms was evaluated by using the 24-item Hamilton Depression Rating Scale (HAMD) in subjects including MDD patients and HC. The participants who met the following criteria were excluded from this study: 1) having severe suicidal tendencies; 2) having neurological or medical illness; 3) having substance dependence; 4) pregnancy or breastfeeding; 5) having some contraindications such as with metallic implants. Following a complete written and oral explanation of this study, each subject provided written consent to participate in the study. All research procedures were performed in accordance with the Declaration of Helsinki on Ethical Principles and were approved by the local Institutional Review Boards of Hangzhou Normal University.

Table 1

Demographic and clinical data.
Characteristics	MDD (Mean ± SD)	HC (Mean ± SD)	p-value
Sex (male/female)	36 (10/26)	43 (16/27)	0.374^a
Age (years)	28.03 ± 10.20	29.42 ± 12.55	0.595^b
Baseline HAMD	27.78 ± 6.70	1.35 ± 1.38	< 0.001^b
3-month HAMD	11.42 ± 7.09
Duration of illness (months)	9.36 ± 14.96
First	25
Recurrence	11
On-medication SSRIs (n patients)	36
The data were presented as the mean ± standard deviation.
Abbreviations: HC, healthy control; MDD, major depressive disorder; HAMD, Hamilton Depression Rating Scale; SSRIs, selective serotonin reuptake inhibitors.
^a The p-value was obtained by a chi-square test;
^b The p-value was obtained by a two-tailed two-sample t-test

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2.2 Antidepressant treatment

The longitudinal data were collected from patients with MDD before and after 3 months of antidepressant pharmacotherapy with selective serotonin reuptake inhibitors (SSRIs). The medication dosages were prescribed and adjusted by the treating psychiatrists according to routine clinical practice and followed the recommended dosages ranges. After 3-month antidepressant treatment, all MDD patients underwent MRI scan and psychiatric assessments including HAMD evaluation again. HC participants didn’t take any medicine and only received the baseline MRI scan. The remission rate (RR%) was defined as (Baseline HAMD scores – 3-month HAMD scores) / Baseline HAMD scores.

2.3 MRI data acquisition

Imaging data of all participants were collected from the 3.0 T Discovery MR 750 scanner (General Electric, Waukesha, WI, USA) at the Center for Cognition and Brain Disorders at Hangzhou Normal University. Subjects were instructed to remain still with their eyes closed, to not think of anything in particular, and to remain awake during the scanning. To fix the head and reduce motion, a pair of stabilizers was used to immobilize the subjects' heads. Functional images were collected in an interleaved order using a T2*-weighted gradient-echo EPI pulse sequence. Detailed acquisition parameters were determined as follows: repetition time (TR) = 2000 ms, echo time (TE) = 22 ms, flip angle = 77°, field of view (FOV) = 240×240 mm², matrix = 96×96, 2.5 mm isotropic spatial resolution with 42 slices and 240 volumes. High-resolution T1-weighted anatomical images were obtained in sagittal orientation for visualization and localization of the functional images with fast spoiled gradient echo sequence (3D FSPGR): TR = 9 ms, TE = 3.66 ms, flip angle = 13°, field of view (FOV) = 240×240 mm², matrix = 300×300, 0.8 mm isotropic voxels, 176 slices without interslice gap.

2.4 MRI preprocessing

The T1-weighted brain structural images were pre-processed and examined using CAT12 (Computational Anatomy Toolbox 12, http://www.neuro.uni-jena.de/cat/) based on the SPM12 software (http://www.fil.ion.ucl.ac.uk/spm/software/spm12). CAT12 is a widely used program for performing voxel-based morphometric (VBM) analysis. In the VBM analysis, we estimated a non-linear deformation field that can best overlays the tissue probability maps on individual participant’s MRI images. The original T1-weighted images were segmented into three tissue components, including the gray matter (GM), the white matter (WM), and the cerebral spinal fluid (CSF). The overall tissue volume and total intracranial volume were calculated in the native space. Afterwards, the segmented GM images and WM images of all participants were used to create a study-specific template by using DARTEL (Diffeomorphic Anatomical Registration using Exponentiated Lie algebra toolbox). The Montreal Neurological Institute (MNI) standard brain template was adopted to achieve normalization of the standard space using modulation, the voxel size for normalized images was 1.5×1.5×1.5 mm³. Finally, the modulated GM tissue segments were smoothed with an 8-mm full width at half maximum (FWHM) isotropic Gaussian kernel. We obtained the smoothed and modulated GM images for each participant to be used in further statistical analysis. In order to exclude the influence of total intracranial volume on statistics, we calculated not only the absolute volume in cubic centimeters, but also the relative volume obtained by dividing the absolute volume by the total cerebral volume (TCV) including the cerebrospinal fluid volume and use them in subsequent analysis.

The processing of original rs-fMRI image data was conducted using a combination of the DPABI software (for Data Processing & Analysis of Brain Imaging, http://rfmri.org/dpabi) and custom code written in MATLAB (The MathWorks, Inc., Natick, MA, United States). The first ten functional volumes of participants were discarded to allow for magnetization equilibration effects and the adaptation of the participants to the circumstances. The remaining images were corrected for time delay between slices and then realigned to the first volume for head motion correction. Throughout the entire scanning process, all participants had a maximum displacement of less than 2 mm in the x-, y-, or z-axes and an angular motion of less than 2°. To further control the confounding effects of head motion, the framewise displacement (FD) across time points was calculated for further analysis. The 3D T1-based transformation was used to perform the spatial normalization of the functional images. The 3D T1 images were co-registered to mean functional images. The corrected images were spatially normalized into the standard stereotactic space of the Montreal Neurological Institute using the transformation derived from T1 segmentation and resampled into 3-mm isotropic voxels. To further reduce the influences of confounding factors, we also regressed out the following sources: six motion parameters, white matter signal and cerebrospinal fluid (CSF) signal. After band-pass filtering (0.01–0.1Hz), we used the cubic spline method, that is moving "bad" time points from the time series with an FD threshold of 0.5mm to reduce the effects of head motion (Liao et al., 2019). All participants’ images were visually inspected for accuracy of segmentation, registration, skull stripping, and cortical surface reconstruction.

2.5 Sliding window dFC analysis of the left rostral hippocampus

Following a brain template from the Human Brainnetome Atlas Project (http://atlas.brainnetome.org), the hippocampus in each hemisphere was divided into 2 subregions: the caudal and rostral hippocampus (Fig. 1). A principal theory of functional differentiation within the hippocampus suggested that the functional role of the hippocampus varies along its longitudinal axis, that is, the anterior hippocampus is responsible for emotional reactions and the posterior hippocampus contribute to cognitive functions (Bonilha et al., 2015). There is substantial evidence demonstrating that the anterior portion of the hippocampus, namely the rostral hippocampus, is highly involved in recollection of previous experience events and retrieval of unpleasant experiences, as well as modulating affective processing in particular of sadness and fear. Whereas the posterior part of the hippocampus, namely the caudal hippocampus, is related to perceptual functioning. Furthermore, encoding in episodic memory uses more anterior regions of the hippocampal formation, whereas spatial navigation utilizes more posterior regions, which suggests a specific role of the anterior hippocampus in remembering emotion-related stimuli. Evolutionary and functional neuroimaging evidence suggests that the right and left hippocampus have functional differences. Most theories suggest that the right hippocampus is more related to nonverbal and spatial functions, while the left hippocampus is more associated with verbal memory functions (Golby et al., 2001; Trenerry et al., 1993). Therefore, based on these characteristics of the hippocampus, we employed the left rostral hippocampus to research the dFC in MDD patients.

-------------------------------- Insert Fig. 1 here -------------------------------

To obtain the whole-brain dFC map of the left rostral hippocampus, we adopted a sliding-window approach for each subject. We used a window created by convolving a rectangle with a Gaussian (σ = 3 TRs) and iteratively sliding each window by 1 TR (2s). In a Gaussian window, the data at the beginning and the end of the window were downweighed. By setting the window size to 22 TRs (44s), we obtained 209 consecutive windows for each participant. To reduce low-frequency excursions and respiratory or cardiac noise at high frequency, the rs-fMRI data of each window were temporally bandpass filtered ([0.01HZ − 0.1HZ]). Within each sliding window, for each seed region of interest (ROI), we calculated the Pearson correlation coefficient between the mean rs-fMRI signal of the left rostral hippocampus and signals of other voxels. The resulting correlation coefficients were converted to z-scores using the Fisher r-to-z transformation to improve normality. Therefore, we obtained 209 z-score maps for each participant, representing the whole-brain dFC fluctuation for the left rostral hippocampus.

2.6 Statistical analysis

The two-sample t-test was employed to analyze the demographic and clinical data. The chi-square test was employed to assess the gender differences between the MDD and HC groups. We performed t-tests to compare dFC differences between MDD patients and HC, and the gender, age, and head movement of all participants were regressed as covariates. In order to control for multiple comparisons, FWE corrections (family-wise error) with Gaussian random field theory were employed with the voxel threshold set to p < 0.001 and the cluster threshold set to p < 0.0125 (0.05/4).”). A two-sample t-test was also used between the differences in the baseline volume of MDD patients, the volume of MDD patients after 3-month medical treatment and the volume of HC. Bonferroni corrections were conducted for multiple comparisons correction. Therefore, we carried out Pearson correlation analysis in the MDD group to explore the relationship between the neuroimaging findings (dFC and volume) and clinical characteristics (HAMD).

To investigate whether the influence of the left rostral hippocampal volume on antidepressant efficacy was mediated by its abnormal dFC, a mediation analysis based on a standard three-variable mediation model was performed, with the relative volume of the left rostral hippocampus as the independent variable, its dFC as the mediator, and the antidepressant efficacy after 3-month treatment as dependent variables. The significance of the mediation effect was assessed using bootstrapping method and bias-corrected 95% confidence intervals (CI) in PROCESS macro (V4) for SPSS (version 25; IBM SPSS Inc.). A confidence interval that does not contain zero means that there exists a significant mediation effect for the proposed mediating factor.

3.1 Demographic and clinical characteristics

The demographic and clinical characteristics of all participants were summarized in Table 1. Two-sample t-tests and a chi-square test were employed to identify the differences among the groups in terms of age, HAMD scores and gender. In the comparison between MDD patients and HC, no significant differences were found in age (p = 0.374) or gender (p = 0.595). The HAMD scores of MDD patients and HC were significantly different (p < 0.001).

3.2 Group differences between MDD and HC

Compared with HC, patients with MDD showed statistically significant decreased dFC of the left rostral hippocampus (rHipp.L) with some brain regions including the right precentral gyrus (PreCG.R, p < 0.0125, FWE-corrected; peak MNI coordinates: x = 48, y = -9, z = 57, t = -5.03, cluster size = 374 voxels), postcentral gyrus (PoCG.L, p < 0.05) and left superior temporal gyrus (STG.L, p < 0.05). Thereinto, the case-control comparison results of the dFC between the rHipp.L and PreCG.R were shown in Fig. 2. There were significant differences in the dFC of the rHipp.L with the PreCG.R between MDD patients at baseline and HC (p < 0.001), as well as between MDD patients after 3-month treatment and HC (p < 0.01). There were no significant differences in the volume of the rHipp.L between MDD and HC (p > 0.05).

-------------------------------- Insert Fig. 2 here -------------------------------

3.3 Correlations and mediation analysis

As shown in Fig. 3, the dFC between the rHipp.L and PreCG.R demonstrated statistically significant associations with the relative volume of the rHipp.L (r = 0.304, p = 0.07) and HAMD remission rate (r = -0.389, p = 0.05) in MDD respectively. Further mediation analysis found that this dFC of the rHipp.L could significantly mediate the relationship between the relative volume of the rHipp.L and HAMD remission rate in MDD patients. Our results revealed that when the rHipp.L relative volume was examined as a possible predicting factor, the total effect c = -0.111, the direct effect c’ = 0.007 (95% CI [-580.12, 604.2]), the indirect effect c – c’ = -0.118 (95% CI [-0.387, -0.003]) the dFC between rHipp.L and PreCG. L was a significant mediator in the relationship between the relative volume of rHipp.L and antidepressant efficacy after 3-month medical treatment in MDD patients (Fig. 3).

-------------------------------- Insert Fig. 3 here -------------------------------

The present study reported the effect of the hippocampal structure and function on antidepressant pharmacotherapy responses for MDD, indicating the dFC of the left rostral hippocampal subregion mediated the relationship between the hippocampal volume and antidepressant efficacy. The findings advanced our understanding of how the hippocampus affects the treatment effects and provided potential biomarkers for treatment prediction and evaluations in MDD.

Many studies have provided consistent evidence of the importance of the hippocampus in the development or treatment of MDD (Hu et al., 2018; Santos et al., 2018; Vakili et al., 2000). Hippocampal volume is proposed as a potentially useful neuroimaging biomarker of treatment sensitivity to antidepressant. One recent research (Maller et al., 2018) revealed that increased hippocampal tail volume could predict depression status and remission to antidepressant medications in MDD, and another research (McKinnon et al., 2009) reported smaller left and right hippocampal volumes in patients with MDD. These findings suggested the importance of using VBM analysis to explore the volume of specific hippocampal subregions. The dFC provided a new tool for exploring the neurophysiological mechanism of MDD. One previous study (Qiu et al., 2018) has also demonstrated altered dFC variability in the medial prefrontal cortex (mPFC) and large-scale functional networks in MDD patients. These findings prompted us that the combined use of VBM and dFC analysis might provide novel understandings of MDD pathology. Therefore, VBM analysis and seed-based dFC analysis were two interrelated analytical methods employed in this study.

In our current research, MDD patients showed lower dFC in the PoCG.L, STG.L and PreCG.R when using the rHipp.L as a seed compared with HC. The next correlation analysis showed that the dFC between the rHipp.L and PreCG.R was significantly negatively correlated to the remission rate of HAMD, which confirmed previous research. The precentral gyrus is the site of the main somatosensory cortex of the human brain that is highly involved in some pivotal cognitive activities, including working memory (Wager & Smith, 2003), implicit learning (Exner et al., 2002) and motor learning (Nitsche et al., 2003). The abnormalities in the structure and function of the precentral gyrus in MDD patients have been revealed in many neuroimaging studies (Guo et al., 2011; Taki et al., 2005; L. Wang et al., 2012). In addition, superior control-related activation of the precentral gyrus is associated with suicide risk in MDD patients (Harms et al., 2019; Minzenberg et al., 2015). Therefore, we have reason to assume that the aberrant dFC between rHipp.L and PreCG.R leads to abnormally excessive suicidal beliefs and suicidal behaviors in MDD patients. Furthermore, the gray matter volume of the precentral gyrus in MDD patients may be related to avoidance motivation, which is one of the most significant characteristics of MDD patients (Li et al., 2017). Most importantly, this was found to be associated with negative attribution bias (Blackwood et al., 2000). Internal attributions of events, where the self is viewed as an active intentional agent, involve PreCG. Aberrant activation of PreCG may lead MDD patients to use fewer “self-service” attribution manners than HC, which may explain the feelings of worthlessness or excessive or inappropriate guilt in MDD patients.

Further correlation analysis revealed that the dFC between PreCG.R and rHipp.L was significantly positively correlated to the relative volume of rHipp.L. Currently, two hypotheses have been proposed to explain the hippocampal volume: the neuroplasticity hypothesis and the neurogenesis hypothesis (Boku et al., 2018). The neuroplasticity hypothesis addresses that the hippocampal volume is decreased by the shortening the length of dendrites and the decreased number and density of spines. The Neurogenesis hypothesis resolves the issue that the hippocampal volume is decreased by the decrease of neurogenesis in the hippocampal dentate gyrus. These two hypotheses assume that, whether from the perspective of morphological changes of hippocampal neurons, or from the perspective of the hippocampal dentate gyrus, as the hippocampus shrinks in patients with MDD, the connectivity of the hippocampus will also decrease, which is verified by our results.

It was worth noting that there were no significant differences between the relative volume of rHipp.L in MDD patients at baseline, after 3-month antidepressant treatment, and HC. Although this appears to be a consensus of the abnormalities of the hypothalamic-pituitary-adrenal (HPA) axis observed in MDD patients, and the hippocampus has been suggested as a suprahypothalamic regulator involved in the negative feedback control of cortisol (Jacobson & Sapolsky, 1991), higher levels of cortisol may induce neuronal damage in the hippocampus, which will cause the hippocampus to shrink. But changes of the hippocampal volume in MDD patients are still a topic of debate. Although smaller hippocampal volume in MDD relative to HC was more frequently reported, some studies have come up with different results. One recent research (Maller et al., 2018) revealed that larger hippocampal tail volume was associated with both a diagnosis of MDD and remission to antidepressant drugs, another study (Axelson et al., 1993) found no differences between the hippocampal volume of nonpsychiatric healthy controls and MDD patients. In our current research, no significant differences were found. This may be the result of a mixed effect of many factors such as the long illness duration, medication effect and MDD patients’ age, and this complicated relationship should be further examined in the future.

After the mediation analysis, the dFC was found to significantly mediate the relationship between the relative volume of rHipp.L and antidepressant efficacy. Because we found abnormal dFC at baseline in MDD patients, and no significant differences in rHipp.L volume were found in group comparisons. It is reasonable to assume that the dFC abnormalities might precede structural abnormalities, suggesting that these imaging phenotypes may indicate distinct stages of cognitive impairment in MDD patients. One study indicated that antidepressant drugs may reverse both the neurogenesis modifications and the impaired neuroplasticity in the hippocampus, such as loss of glial cells and dendritic atrophy (Serafini, 2012), which may normalize the shrunken hippocampus. More importantly, many studies (Chen et al., 2018; Wu et al., 2022; Xiao et al., 2021) have proved that after different phases of antidepressant treatment, even only two weeks, the FC using the hippocampus as a seed improved to varying degrees. We proposed that such a normalization process in the hippocampal connectivity may lead to a beneficial impact on emotional regulation functions and cognitive ability in MDD patients. At the same time, these findings further proved the importance of using dFC as a mediation variable to explore the relationship between the specific hippocampal subregion volume and antidepressant efficacy.

Several limitations of our current research should be solved. Firstly, the antidepressant treatment effect in the present study was for pharmacological treatment and the treatment effect of other treatment protocols is worthy of being studied carefully. Secondly, the sample size of MDD patients was relatively small, which might reduce the generalizability of the work, and our study should be regarded as a pilot study. Future longitudinal studies with large sample sizes and patients with various clinical features are needed to recapitulate the results of our study before they can be applied in clinical practice.

The present study revealed the abnormal dFC between PreCG.R and rHipp.L in MDD patients, although no volume changes were yet detected. Furthermore, the dFC mediated the relationship between the rHipp.L volume and antidepressant efficacy, suggesting that there exist temporal dynamics of functional and structural alterations in the disease progression of MDD patients. Most importantly, our research showed that a combination of volume and abnormal dFC yielded higher discriminative value in predicting antidepressant efficacy in MDD patients compared with either alone. Our current research expanded our understanding of the brain circuits related to the antidepressant efficacy of MDD, revealed the importance of the volume and dFC of specific hippocampal subregion as a neuroimaging biomarker, provided new evidence supporting the application of neuroimaging techniques in the treatment outcome prediction thus guide more individualized treatment strategy for MDD patients.

Acknowledgments This work was supported by the Natural Science Foundation of Zhejiang Province (LY17H180007), the National Natural Science Foundation of China (81271503), Key Medical Disciplines of Hangzhou, and Zhejiang Medical and Health Science and Technology Project (2022490271). The authors thank the teachers and students who assisted in the experiment and data collection.

Credit author statement Changxiao Kuai and Jiayong Pu:Data Analysis, Visualization, Writing – Original Draft Preparation. Donglin Wang, Zhonglin Tan and Yan Wang: Data collection. Shao-Wei Xue: Writing – Review & Editing.

Data availability statement The data that support the findings of this study are available from the corresponding author upon reasonable request.

Competing interests The authors declare that they have no conflicts of interest in the manuscript.

Ethical Approval The studies involving human participants were reviewed and approved by the Institutional Review Boards of Hangzhou Normal University.

Informed consent The patients/participants provided their written informed consent to participate in this study.

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No competing interests reported.

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The dynamic functional connectivity of the left rostral hippocampus involved in mediating the association between hippocampal volume and antidepressant efficacy in major depressive disorder

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Abstract

Figures

1. Introduction

2. Methods

2.1 Participants

2.2 Antidepressant treatment

2.3 MRI data acquisition

2.4 MRI preprocessing

2.5 Sliding window dFC analysis of the left rostral hippocampus

2.6 Statistical analysis

3. Results

3.1 Demographic and clinical characteristics

3.2 Group differences between MDD and HC

3.3 Correlations and mediation analysis

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

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