Altered Functional Magnetic Resonance Imaging Markers of Affective Processing During Treatment of Late-Life Depression

Neural signatures of default mode network in major depression disorder after electroconvulsive therapy

Functional abnormalities of default mode network (DMN) have been well documented in major depressive disorder (MDD). However, the association of DMN functional reorganization with antidepressant treatment and gene expression is unclear. Moreover, whether the functional interactions of DMN could predict treatment efficacy is also unknown. Here, we investigated the link of treatment response with functional alterations of DMN and gene expression with a comparably large sample including 46 individuals with MDD before and after electroconvulsive therapy (ECT) and 46 age- and sex-matched healthy controls. Static and dynamic functional connectivity (dFC) analyses showed increased intrinsic/static but decreased dynamic functional couplings of inter- and intra-subsystems and between nodes of DMN. The changes of static functional connections of DMN were spatially correlated with brain gene expression profiles. Moreover, static and dFC of the DMN before treatment as features could predict depressive symptom improvement following ECT. Taken together, these results shed light on the underlying neural and genetic basis of antidepressant effect of ECT and the intrinsic functional connectivity of DMN have the potential to serve as prognostic biomarkers to guide accurate personalized treatment.

Abnormal dynamics of resting-state functional activity and couplings in postpartum depression with and without anxiety

Postpartum depression (PPD) and PPD comorbid with anxiety (PPD-A) are highly prevalent and severe mental health problems in postnatal women. PPD and PPD-A share similar pathopsychological features, leading to ongoing debates regarding the diagnostic and neurobiological uniqueness. This paper aims to delineate common and disorder-specific neural underpinnings and potential treatment targets for PPD and PPD-A by characterizing functional dynamics with resting-state functional magnetic resonance imaging in 138 participants (45 first-episode, treatment-naïve PPD; 31 PDD-A patients; and 62 healthy postnatal women [HPW]). PPD-A group showed specifically increased dynamic amplitude of low-frequency fluctuation in the subgenual anterior cingulate cortex (sgACC) and increased dynamic functional connectivity (dFC) between the sgACC and superior temporal sulcus. PPD group exhibited specifically increased static FC (sFC) between the sgACC and ventral anterior insula. Common disrupted sFC between the sgACC and middle temporal gyrus was found in both PPD and PPD-A patients. Interestingly, dynamic changes in dFC between the sgACC and superior temporal gyrus could differentiate PPD, PPD-A, and HPW. Our study presents initial evidence on specifically abnormal functional dynamics of limbic, emotion regulation, and social cognition systems in patients with PDD and PPD-A, which may facilitate understanding neurophysiological mechanisms, diagnosis, and treatment for PPD and PPD-A.

Postpartum depression and major depressive disorder: the same or not? Evidence from resting-state functional MRI

Background

Although postpartum depression (PPD) and non-peripartum major depressive disorder (MDD) occurring within and outside the postpartum period share many clinical characteristics, whether PPD and MDD are the same or not remains controversial.

Methods

The current study was devoted to identify the shared and different neural circuits between PPD and MDD by resting-state functional magnetic resonance imaging data from 77 participants (22 first-episodic drug-naïve MDD, 26 drug-naïve PPD, and 29 healthy controls (HC)).

Results

Both the PPD and MDD groups exhibited higher fractional amplitude of low-frequency fluctuation (fALFF) in left temporal pole relative to the HC group; the MDD group showed specifically increased degree centrality in the right cerebellum while PPD showed specifically decreased fALFF in the left supplementary motor area and posterior middle temporal gyrus (pMTG_L), and specifically decreased functional connectivities between pMTG and precuneus and between left subgeneual anterior cingulate cortex (sgACC_L) and right sgACC. Moreover, sgACC and left thalamus showed abnormal regional homogeneity of functional activities between any pair of HC, MDD, and PPD.

Conclusions

These results provide initial evidence that PPD and MDD have common and distinct neural circuits, which may facilitate understanding the neurophysiological basis and precision treatment for PPD.

MRI predictors of pharmacotherapy response in major depressive disorder

Major depressive disorder is among the most prevalent psychiatric disorders, exacting a substantial personal, social, and economic toll. Antidepressant treatment typically involves an individualized trial and error approach with an inconsistent success rate. Despite a pressing need, no reliable biomarkers for predicting treatment outcome have yet been discovered. Brain MRI measures hold promise in this regard, though clinical translation remains elusive. In this review, we summarize structural MRI and functional MRI (fMRI) measures that have been investigated as predictors of treatment outcome. We broadly divide these into five categories including three structural measures: volumetric, white matter burden, and white matter integrity; and two functional measures: resting state fMRI and task fMRI. Currently, larger hippocampal volume is the most widely replicated predictor of successful treatment. Lower white matter hyperintensity burden has shown robustness in late life depression. However, both have modest discriminative power. Higher fractional anisotropy of the cingulum bundle and frontal white matter, amygdala hypoactivation and anterior cingulate cortex hyperactivation in response to negative emotional stimuli, and hyperconnectivity within the default mode network (DMN) and between the DMN and executive control network also show promise as predictors of successful treatment. Such network-focused measures may ultimately provide a higher-dimensional measure of treatment response with closer ties to the underlying neurobiology.

The functional and structural connectomes associated with geriatric depression and anxiety symptoms in mild cognitive impairment: Cross-syndrome overlap and generalization

Geriatric depression and anxiety disorders often manifest as neuropsychiatric symptoms among those with mild cognitive impairment. Both tend to co-occur, and overlap in symptomology and etiology. Such commonalities are likely to be reflected in the brain as common neural correlates. Using connectome-based predictive modeling (CPM), we examined the functional and structural connectomes predicting depression and anxiety symptoms, and subsequently the overlap and cross-syndrome generalization of the connectomes associated with either disorder. Ninety-one older adults completed self-reported measures of depression and anxiety, and underwent diffusion tensor imaging and resting-state functional magnetic resonance imaging. Functional connectivity (FC) and structural connectivity (SC) matrices were derived from these scans and, in various combinations, entered into CPM models to predict either type of symptoms. Leave-one-out cross-validation was performed. Predictive accuracy was assessed via the correlation between predicted and observed scores (ρ_{predicted-observed}). While FC or SC features alone significantly predicted either type of symptoms, these symptoms were best predicted by models that consisted of both FC and SC features (depression: ρ_{predicted-observed} = 0.497; anxiety: ρ_{predicted-observed} = 0.455). The features common to depression and anxiety were identified and entered into another model which was similarly accurate in predicting either type of symptoms. Moreover, cross-syndrome generalization was observed- the depression-associated features significantly predicted anxiety symptoms (ρ_{predicted-observed} = 0.403) and vice-versa (ρ_{predicted-observed} = 0.378). These FC and SC features are complementary biomarkers of geriatric depression and anxiety symptoms. Both types of symptoms are largely underpinned by common patterns of altered FC and SC, alluding to the transdiagnostic neurobiological susceptibility in both disorders.

Locations for noninvasive brain stimulation in treating depressive disorders: A combination of meta-analysis and resting-state functional connectivity analysis

OBJECTIVE

Many noninvasive brain stimulation techniques have been applied to treat depressive disorders. However, the target brain region in most noninvasive brain stimulation studies is the dorsolateral prefrontal cortex. Exploring new stimulation locations may improve the efficacy of noninvasive brain stimulation for depressive disorders. We aimed to explore potential noninvasive brain stimulation locations for depressive disorders through a meta-analysis and a functional connectivity approach.

METHODS

We conducted a meta-analysis of 395 functional magnetic resonance imaging studies to identify depressive disorder-associated brain regions as regions of interest. Then, we ran resting-state functional connectivity analysis with three different pipelines in 40 depression patients to find brain surface regions correlated with these regions of interest. The 10-20 system coordinates corresponding to these brain surface regions were considered as potential locations for noninvasive brain stimulation.

RESULTS

The 10-20 system coordinates corresponding to the bilateral dorsolateral prefrontal cortex, bilateral inferior frontal gyrus, medial prefrontal cortex, supplementary motor area, bilateral supramarginal gyrus, bilateral primary motor cortex, bilateral operculum, left angular gyrus and right middle temporal gyrus were identified as potential locations for noninvasive brain stimulation in depressive disorders. The coordinates were: posterior to F3, posterior to F4, superior to F3, posterior to F7, anterior to C4, P3, midpoint of F7-T3, posterior to F8, anterior to C3, midpoint of Fz-Cz, midpoint of Fz-Fp1, anterior to T4, midpoint of C3-P3, and anterior to C4.

CONCLUSION

Our study identified several potential noninvasive brain stimulation locations for depressive disorders, which may serve as a basis for future clinical investigations.

Acute trajectories of neural activation predict remission to pharmacotherapy in late-life depression

Pharmacological treatment of major depressive disorder (MDD) typically involves a lengthy trial and error process to identify an effective intervention. This lengthy period prolongs suffering and worsens all-cause mortality, including from suicide, and is typically longer in late-life depression (LLD). Our group has recently demonstrated that during an open-label venlafaxine (serotonin-norepinephrine reuptake inhibitor) trial, significant changes in functional resting state connectivity occurred following a single dose of treatment, which persisted until the end of the trial. In this work, we propose an analysis framework to translate these perturbations in functional networks into predictors of clinical remission. Participants with LLD (N = 49) completed 12-weeks of treatment with venlafaxine and underwent functional magnetic resonance imaging (fMRI) at baseline and a day following a single dose of venlafaxine. Data was collected at rest as well as during an emotion reactivity task and an emotion regulation task. Remission was defined as a Montgomery-Asberg Depression Rating Scale (MADRS) ≤10 for two weeks. We computed eigenvector centrality (whole brain connectivity) and activation during the emotion regulation and emotion reactivity tasks. We employed principal components analysis, Tikhonov-regularized logistic classification, and least angle regression feature selection to predict remission by the end of the 12-week trial. We utilized ten-fold cross-validation and Receiver Operator Curves (ROC) curve analysis. To determine task-region pairs that significantly contributed to the algorithm's ability to predict remission, we used permutation testing. Using the fMRI data at both baseline and after the first dose of treatment yielded a sensitivity of 72% and a specificity of 68% (AUC = 0.77), a 15% increase in accuracy over baseline MADRS. In general, the accuracy at baseline was further improved by using the change in activation following a single dose. Activation of the frontal cortex, hippocampus, parahippocampus, caudate, thalamus, medial temporal cortex, middle cingulate, and visual cortex predicted treatment remission. Acute, dynamic trajectories of functional imaging metrics in response to a pharmacological intervention are a valuable tool for predicting treatment response in late-life depression and elucidating the mechanism of pharmacological therapies in the context of the brain's functional architecture.

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Neural activation changes after a single dose of antidepressants have been observed.

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Patients with late-life depression were treated with an antidepressant for 12 weeks.

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Neuroimaging data was recorded pre-treatment and after a single dose.

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Pre-treatment neuroimaging predicted remission at the end of the trial.

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Neuroimaging after a single dose improved prediction and may guide treatment.

The Abnormal Functional Connectivity between the Hypothalamus and the Temporal Gyrus Underlying Depression in Alzheimer's Disease Patients

Hypothalamic communication with the rest of the brain is critical for accomplishing a wide variety of physiological and psychological functions, including the maintenance of neuroendocrine circadian rhythms and the management of affective processes. Evidence has shown that major depressive disorder (MDD) patients exhibit increased functioning of the hypothalamic-pituitary-adrenal (HPA) axis. Neurofibrillary tangles are also found in the hypothalamus of Alzheimer’s disease (AD) patients, and AD patients exhibit abnormal changes in the HPA. However, little is known of how the hypothalamus interacts with other brain regions in AD patients with depression (D-AD). Functional connectivity (FC) analysis explores the connectivity between brain regions that share functional properties. Here, we used resting-state (rs) magnetic resonance imaging (MRI) technology and the FC method to measure hypothalamic connectivity across the whole brain in 22 D-AD patients and 21 non-depressed AD patients (nD-AD). Our results showed that D-AD patients had reduced FC among the hypothalamus, the right middle temporal gyrus (MTG) and the right superior temporal gyrus (STG) compared with the FC of nD-AD patients, suggesting that the abnormal FC between the hypothalamus and the temporal lobe may play a key role in the pathophysiology of depression in AD patients.