Anterior cingulate cortex and cerebellar hemisphere neurometabolite changes in depression treatment: A 1H magnetic resonance spectroscopy study

Evaluating metabolites in patients with major depressive disorder who received mindfulness-based cognitive therapy and healthy controls using short echo MRSI at 7 Tesla

Objectives

Our aim was to evaluate differences in metabolite levels between unmedicated patients with major depressive disorder (MDD) and healthy controls, to assess changes in metabolites in patients after they completed an 8-week course of mindfulness-based cognitive therapy (MBCT), and to exam the correlation between metabolites and depression severity.

Materials and methods

Sixteen patients with MDD and ten age- and gender-matched healthy controls were studied using 3D short echo-time (20 ms) magnetic resonance spectroscopic imaging (MRSI) at 7 Tesla. Relative metabolite ratios were estimated in five regions of interest corresponding to insula, anterior cingulate cortex (ACC), caudate, putamen, and thalamus.

Results

In all cases, MBCT reduced severity of depression. The ratio of total choline-containing compounds/total creatine (tCr) in the right caudate was significantly increased compared to that in healthy controls, while ratios of N-acetyl aspartate (NAA)/tCr in the left ACC, myo-inositol/tCr in the right insula, and glutathione/tCr in the left putamen were significantly decreased. At baseline, the severity of depression was negatively correlated with my-inositol/tCr in the left insula and putamen. The improvement in depression severity was significantly associated with changes in NAA/tCr in the left ACC.

Conclusions

This study has successfully evaluated regional differences in metabolites for patients with MDD who received MBCT treatment and in controls using 7 Tesla MRSI.

Neurometabolic characteristics in the anterior cingulate gyrus of Alzheimer's disease patients with depression: a (1)H magnetic resonance spectroscopy study

BACKGROUND

Depression is a common comorbid psychiatric symptom in patients with Alzheimer's disease (AD), and the prevalence of depression is higher among people with AD compared with healthy older adults. Comorbid depression in AD may increase the risk of cognitive decline, impair patients' function, and reduce their quality of life. However, the mechanisms of depression in AD remain unclear. Here, our aim was to identify neurometabolic characteristics in the brain that are associated with depression in patients with mild AD.

METHODS

Thirty-seven patients were evaluated using the Neuropsychiatric Inventory (NPI) and Hamilton Depression Rating Scale (HAMD-17), and divided into two groups: 17 AD patients with depression (D-AD) and 20 non-depressed AD patients (nD-AD). Using proton magnetic resonance spectroscopy, we characterized neurometabolites in the anterior cingulate gyrus (ACG) of D-AD and nD-AD patients.

RESULTS

Compared with nD-AD patients, D-AD patients showed lower N-acetylaspartate/creatine (NAA/Cr) and higher myo-inositol/creatine (mI/Cr) in the left ACG. NPI score correlated with NAA/Cr and mI/Cr in the left ACG, while HAMD correlated with NAA/Cr.

CONCLUSIONS

Our findings show neurometabolic alterations in D-AD patients. Thus, D-AD pathogenesis may be attributed to abnormal activity of neurons and glial cells in the left ACG.

Evaluation of Myo-Inositol as a Potential Biomarker for Depression in Schizophrenia

Depression is highly prevalent in patients with schizophrenia and is associated with significant clinical consequences, but there is no known biomarker for depression in schizophrenia. One of the putative neurochemical biomarkers for depression in major depressive disorder (MDD) is reduced cerebral concentration of myo-Inositol. We examined whether myo-Inositol levels provide a potential marker for depressive symptoms in schizophrenia similar to that in MDD and are informative regarding causal biological pathways underlying both depression and schizophrenia. We used proton magnetic resonance spectroscopy to examine myo-Inositol levels in the anterior cingulate cortex (ACC) in 59 schizophrenia spectrum disorder (SSD) patients and 69 matched community comparison participants. Participants completed the Maryland Trait and State Depression (MTSD) scale to measure symptoms of depression experienced around time of assessment ('State' subscale) and longitudinally ('Trait' subscale). Myo-Inositol in the ACC was negatively correlated with MTSD-Trait scores in both patients (ρ=-0.336, p=0.009) and community comparison samples (ρ=-0.328, p=0.006). Furthermore, patients with a diagnosis of schizoaffective disorder or a history of at least one major depressive episode had lower levels of myo-Inositol compared with schizophrenia patients without a current or past affective diagnosis (p=0.012). Since reduced brain myo-Inositol is associated with MDD, myo-Inositol may be a biochemical marker of depressive mood symptoms across diagnostic boundaries. If confirmed, this finding may aid investigation of the pathophysiology and therapeutics of depression common between depression, schizophrenia and other psychiatric diagnoses.

Multimodal approaches to define network oscillations in depression

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients.

Cluster analysis reveals abnormal hippocampal neurometabolic profiles in young people with mood disorders

While numerous studies have employed magnetic resonance spectroscopy (MRS) to determine in vivo neurometabolite levels associated with mood disorders the findings in both unipolar depression and bipolar disorder have been mixed. Data-driven studies may shed new light on this literature by identifying distinct subgroups of patients who may benefit from different treatment strategies. The objective of the present study was to utilize hierarchical cluster analysis in order to generate new hypotheses with respect to neurometabolic profiling of mood disorder. Participants were 165 young persons (18-30 yrs) with a mood disorder and 40 healthy controls. Neurometabolite levels were recorded via proton-MRS ((1)H MRS). The ratios (relative to creatine) of glutamate (GLU), N-acetyl aspartate (NAA) and myo-inositol (MI) measured within the hippocampus. Self-reported and clinician rated symptoms as well as cognition were also measured. The unipolar depression (N=90) and bipolar disorder (N=75) groups did not significantly differ (from each other or controls) in their levels of GLU, NAA or MI. Cluster analyses derived four subgroups of patients who were distinguished by all three metabolites. There was a pattern of positive association between NAA and GLU, whereby clusters were abnormally increased (clusters 1, 2) or normal (cluster 4) or abnormally decreased (cluster 3) in these neurometabolites. These findings suggest that there are neurometabolic abnormalities in subgroups of young people with mood disorder, which may occur despite diagnostic similarities. Such evidence highlights that the underlying neurobiology of mood disorder is complex and MRS may have unique utility in delineating underlying neurobiology and targeting treatment strategies.

Could glutamate spectroscopy differentiate bipolar depression from unipolar?

BACKGROUND

Accurate differentiation of bipolar and unipolar depression is a key clinical challenge. A biological measure that could differentiate bipolar and unipolar depression might supplement clinical assessment. Magnetic Resonance Spectroscopy measurements of total glutamate and glutamine (Glx) in anterior cingulate cortex are one potential measure. The objective of this study was to assess the potential performance of this measure.

METHODS

Meta-analysis of data from eleven studies where anterior cingulate Glx of depressed patients has been compared to that of healthy controls was performed. Effect sizes for bipolar and unipolar depression were calculated as Standardised Mean Differences. The best estimate of test classification performance on the basis of observed effects was calculated.

RESULTS

People with unipolar depression had on average lower levels of Glx than healthy controls (effect size -1.05; 95% CI -058 to -1.53). People with bipolar depression tended towards higher Glx than healthy controls (effect size 0.40; 95% CI -0.04 to 0.85). This yielded a difference in Glx between unipolar and bipolar depression of effect size 1.46 (95% CI 0.80-2.11). Based on this difference, a test differentiating bipolar from unipolar depression by whether Glx was higher or lower than the average in healthy population would have sensitivity 0.66 and specificity 0.85.

LIMITATIONS

There is an absence of studies directly comparing unipolar and bipolar depressed patients.

CONCLUSIONS

On available data, measurement of anterior cingulate Glx is a promising potential tool for differentiation of bipolar and unipolar depression. This potential effect requires direct validation within mixed clinical cohorts.