Altered electroencephalography resting state network coherence in remitted MDD.

Individuals with remitted depression are at greater risk for subsequent depression and therefore may provide a unique opportunity to understand the neurophysiological correlates underlying the risk of depression. Research has identified abnormal resting-state electroencephalography (EEG) power metrics and functional connectivity patterns associated with major depression, however little is known about these neural signatures in individuals with remitted depression. We investigate the spectral dynamics of 64-channel EEG surface power and source-estimated network connectivity during resting states in 37 individuals with depression, 56 with remitted depression, and 49 healthy adults that did not differ on age, education, and cognitive ability across theta, alpha, and beta frequencies. Average reference spectral EEG surface power analyses identified greater left and midfrontal theta in remitted depression compared to healthy adults. Using Network Based Statistics, we also demonstrate within and between network alterations in LORETA transformed EEG source-space coherence across the default mode, fronto-parietal, and salience networks where individuals with remitted depression exhibited enhanced coherence compared to those with depression, and healthy adults. This work builds upon our currently limited understanding of resting EEG connectivity in depression, and helps bridge the gap between aberrant EEG power and brain network connectivity dynamics in this disorder. Further, our unique examination of remitted depression relative to both healthy and depressed adults may be key to identifying brain-based biomarkers for those at high risk for future, or subsequent depression.

(Es)Ketamine for Suicidal Ideation and Behavior: Clinical Efficacy.

Suicidal ideation and behavior are among the most severe psychiatric presentations, warranting emergency room visits and psychiatric admission for higher levels of care. In the United States, suicide rates continue to climb, especially in younger patients, and the continued psychosocial stressors of the COVID-19 pandemic may further exacerbate this crisis. Suicidal ideation and behavior are core features of a major depressive episode, but there are limited treatment options to rapidly redress these life-threatening symptoms. Racemic ketamine and its S-enantiomer, esketamine, are N-methyl-D-aspartate receptor antagonists and glutamate modulators that have robust antidepressant efficacy in treatment-resistant major depressive disorder and bipolar depression. Additionally, both ketamine and esketamine have demonstrated rapid-acting antisuicidal efficacy in major mood disorders. In August 2020, this culminated in a first-in-class approval of Spravato® (intranasal esketamine) for the treatment of major depressive disorder with acute suicidal ideation and behavior. In this article, we review the literature in support of the antisuicidal efficacy of ketamine and esketamine.

DNA methylation in the TNF-alpha gene decreases along with aging among delirium inpatients.

It has been suggested that aging and inflammation play key roles in the development of delirium. In the present study, we investigated the differences of the DNAm patterns in the TNF gene between patients with delirium and without. The data and samples derived from previous and ongoing cohort studies were analyzed. DNAm levels of the TNF gene were analyzed using the Illumina EPIC array genome-wide method and pyrosequencing method. Correlations between age and DNAm levels of each CpG were calculated. Several CpG in the TNF gene in blood showed negative correlation between their DNAm and age in delirium cases both with the EPIC array and by the pyrosequencing method. However, there was no CpG that had significant correlation between their DNAm and age regardless of delirium status among buccal samples. On the other hand, among peripheral blood mononuclear cells samples, it was found that several CpG showed negative correlation between their DNAm and age in delirium cases. The evidence of DNAm change in the TNF gene among delirious subjects was demonstrated.

Biomarkers of ketamine's antidepressant effect: a clinical review of genetics, functional connectivity, and neurophysiology.

Major depressive disorder (MDD) is one of the leading causes of morbidity and all-cause mortality (including suicide) worldwide, and, unfortunately, first-line monoaminergic antidepressants and evidence-based psychotherapies are not effective for all patients. Subanesthetic doses of the N-methyl-D-aspartate receptor antagonists and glutamate modulators ketamine and S-ketamine have rapid and robust antidepressant efficacy in such treatment-resistant depressed patients (TRD). Yet, as with all antidepressant treatments including electroconvulsive therapy (ECT), not all TRD patients adequately respond, and we are presently unable to a priori predict who will respond or not respond to ketamine. Therefore, antidepressant treatment response biomarkers to ketamine have been a major focus of research for over a decade. In this article, we review the evidence in support of treatment response biomarkers, with a particular focus on genetics, functional magnetic resonance imaging, and neurophysiological studies, i.e. electroencephalography and magnetoencephalography. The studies outlined here lay the groundwork for replication and dissemination.

Multifactorial prediction of depression diagnosis and symptom dimensions.

While depression is a leading cause of disability, prior investigations of depression have been limited by studying correlates in isolation. A data-driven approach was applied to identify out-of-sample predictors of current depression from adults (N = 217) sampled on a continuum of no depression to clinical levels. The current study used elastic net regularized regression and predictors from sociodemographic, self-report, polygenic scores, resting electroencephalography, pupillometry, actigraphy, and cognitive tasks to classify individuals into currently depressed (MDE), psychiatric control (PC), and no current psychopathology (NP) groups, as well as predicting symptom severity and lifetime MDE. Cross-validated models explained 20.6% of the out-of-fold deviance for the classification of MDEs versus PC, 33.2% of the deviance for MDE versus NP, but -0.6% of the deviance between PC and NP. Additionally, predictors accounted for 25.7% of the out-of-fold variance in anhedonia severity, 65.7% of the variance in depression severity, and 12.9% of the deviance in lifetime depression (yes/no). Self-referent processing, anhedonia, and psychosocial functioning emerged as important differentiators of MDE and PC groups. Findings highlight the advantages of using psychiatric control groups to isolate factors specific to depression.

Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: A data-driven approach.

BACKGROUND: Individual differences in reward-related processes, such as reward responsivity and approach motivation, appear to play a role in the nature and course of depression. Prior work suggests that cognitive biases for valenced information may contribute to these reward processes. Yet there is little work examining how biased attention, processing, and memory for positively and negatively valenced information may be associated with reward-related processes in samples with depression symptoms. METHODS: We used a data-driven, machine learning (elastic net) approach to identify the best predictors of self-reported reward-related processes using multiple tasks of attention, processing, and memory for valenced information measured across behavioral, eye tracking, psychophysiological, and computational modeling approaches (n = 202). Participants were adults (ages 18-35) who ranged in depression symptom severity from mild to severe. RESULTS: Models predicted between 5.0-12.2% and 9.7-28.0% of held-out test sample variance in approach motivation and reward responsivity, respectively. Low self-referential processing of positively valenced information was the most robust, albeit modest, predictor of low approach motivation and reward responsivity. CONCLUSIONS: Self-referential processing of positive information is the strongest predictor of reward responsivity and approach motivation in a sample ranging from mild to severe depression symptom severity. Experiments are now needed to clarify the causal relationship between self-referential processing of positively valenced information and reward processes in depression.