Sex Differences in Anxiety: An Investigation of the Moderating Role of Sex in Performance Monitoring and Attentional Bias to Threat in High Trait Anxious Individuals

Disorder-specific versus transdiagnostic cognitive mechanisms in anxiety and depression: Machine-learning-based prediction of symptom severity

INTRODUCTION

Psychiatric evaluation of anxiety and depression is currently based on self-reported symptoms and their classification into discrete disorders. Yet the substantial overlap between these disorders as well as their within-disorder heterogeneity may contribute to the mediocre success rates of treatments. The proposed research examines a new framework for diagnosis that is based on alterations in underlying cognitive mechanisms. In line with the Research Domain Criteria (RDoC) approach, the current study directly compares disorder-specific and transdiagnostic cognitive patterns in predicting the severity of anxiety and depression symptoms.

METHODS

The sample included 237 individuals exhibiting differing levels of anxiety and depression symptoms, as measured by the STAI-T and BDI-II. Random Forest regressors were used to analyze their performance on a battery of six computerized cognitive-behavioral tests targeting selective and spatial attention, expectancy, interpretation, memory, and cognitive control biases.

RESULTS

Unique anxiety-specific biases were found, as well as shared anxious-depressed bias patterns. These cognitive biases exhibited relatively high fitting rates when predicting symptom severity (questionnaire scores common range 0-60, MAE = 6.03, RMSE = 7.53). Interpretation and expectancy biases exhibited the highest association with symptoms, above all other individual biases.

LIMITATIONS

Although internal validation methods were applied, models may suffer from potential overfitting due to sample size limitations.

CONCLUSION

In the context of the ongoing dispute regarding symptom-centered versus transdiagnostic approaches, the current study provides a unique comparison of these two views, yielding a novel intermediate approach. The results support the use of mechanism-based dimensional diagnosis for adding precision and objectivity to future psychiatric evaluations.

Effects of online mindfulness-based interventions (MBIs) on anxiety symptoms in adults: a systematic review and meta-analysis

BACKGROUND

An increasing number of studies have documented the effectiveness on various types of face-to-face and online mindfulness-based interventions (MBIs) in reducing anxiety among general population, but there is a scarcity of systematic reviews evaluating evidence of online MBIs on anxiety in adults. Therefore, we examined the effects of online mindfulness-based interventions (MBIs) on anxiety symptoms in adults and explored the moderating effects of participant, methods, and intervention characteristics.

METHODS

We systematically searched nine databases through May 2022 without date restrictions. Inclusion criteria were primary studies evaluating online mindfulness-based interventions with adults with anxiety measured as an outcome, a comparison group, and written in English. We used random-effects model to compute effect sizes (ESs) using Hedges' g, a forest plot, and Q and I² statistics as measures of heterogeneity; we also examined moderator analyses.

RESULTS

Twenty-six primary studies included 3,246 participants (39.9 ± 12.9 years old). Overall, online mindfulness-based interventions showed significantly improved anxiety (g = 0.35, 95%CI 0.09, 0.62, I² = 92%) compared to controls. With regards to moderators, researchers reported higher attrition, they reported less beneficial effects on anxiety symptoms (β=-0.001, Q_model=4.59, p = .032). No other quality indicators moderated the effects of online mindfulness-based interventions on anxiety.

CONCLUSION

Online mindfulness-based interventions improved anxiety symptoms in adult population. Thus, it might be used as adjunctive or alternative complementary treatment for adults. However, our findings must be interpreted with caution due to the low and unclear power of the sample in primary studies; hence, high-quality studies are needed to confirm our findings.

The gray matter morphology associated with the electrophysiological response to errors in individuals with high trait anxiety

Enhanced error monitoring has been associated with higher levels of anxiety. This has been consistently demonstrated in its most reliable electrophysiological index, the error-related negativity (ERN), such that increased ERN is related with elevated anxiety symptomology. However, it is still unclear whether the structural properties of the brain are associated with individual differences in ERN amplitude. Moreover, the relationship between ERN and anxiety has recently been suggested to be moderated by sex, but the degree to which sex moderates the association between brain structure and ERN amplitude is unknown. The present study investigated the association between gray matter volume (GMV) and ERN amplitude in individuals with high trait anxiety (N = 98) as well as the role of sex in moderating this association. The ERN was elicited from a flanker task, whereas structural MRI images were obtained from whole brain structural T1-weighted MRI scans. The results of voxel-based morphometry analyses showed that the relationship between ERN difference scores and GMV was moderated by sex in the dorsal anterior cingulate cortex (dACC). This sex difference was derived from a negative correlation between ERN difference scores and dACC GMV in females and a positive correlation in males. Our findings are in accordance with the critical role of the dACC serving as a neural substrate of error monitoring. It also provides further evidence for sex-specific associations with brain structures related to error monitoring.

The questionable validity of attention bias variability: Evidence from two conceptually unrelated cognitive tasks

Background

Attention bias variability is thought to measure fluctuations in attention towards and away from threat-related information and is elevated in affective disorders. However, recent evidence suggests that attention bias variability may quantify general reaction time variability rather than attention bias behavior per se.

Methods

The current study calculated "attention bias variability" from two conceptually unrelated cognitive tasks: the dot-probe task (measuring attentional bias) and the arrow flanker task (measuring cognitive control).

Results

Attention bias variability measures were correlated across these unrelated tasks. Yet, when general reaction time variability was controlled, attention bias variability across tasks was no longer correlated. In addition, the reliability of attention bias variability measures decreased when controlling for general reaction time variability. Finally, although attention bias variability calculated from the dot-probe task initially correlated with anxious symptoms, this association was no longer significant when controlling for general reaction time variability.

Limitations

Our sample was comprised of high trait anxious individuals. Replication in clinical samples is warranted.

Conclusions

These findings collectively provide strong empirical evidence that attention bias variability is not a valid measure of attention-related behavior, but reflective of general reaction time variability more broadly.

miR-218: A Stress-Responsive Epigenetic Modifier

Understanding the epigenetic role of microRNAs (miRNAs) has been a critical development in the field of neuropsychiatry and in understanding their underlying pathophysiology. Abnormalities in miRNA expression are often seen as key to the pathogenesis of many stress-associated mental disorders, including major depressive disorder (MDD). Recent advances in omics biology have further contributed to this understanding and expanded the role of miRNAs in networking a diverse array of molecular pathways, which are essentially related to the stress adaptivity of a healthy brain. Studies have highlighted the role of many such miRNAs in causing maladaptive changes in the brain's stress axis. One such miRNA is miR-218, which is debated as a critical candidate for increased stress susceptibility. miR-218 is expressed throughout the brain, notably in the hippocampus and prefrontal cortex (PFC). It is expressed at various levels through life stages, as seen by adolescent and adult animal models. Until now, a minimal number of studies have been conducted on human subjects to understand its role in stress-related abnormalities in brain circuits. However, several studies, including animal and cell-culture models, have been used to understand the impact of miR-218 on stress response and hypothalamic-pituitary-adrenal (HPA) axis function. So far, expression changes in this miRNA have been found to regulate signaling pathways such as glucocorticoid signaling, serotonergic signaling, and glutamatergic signaling. Recently, the developmental role of miR-218 has generated interest, given its increasing expression from adolescence to adulthood and targeting the Netrin-1/DCC signaling pathway. Since miR-218 expression affects neuronal development and plasticity, it is expected that a change in miR-218 expression levels over the course of development may negatively impact the process and make individuals stress-susceptible in adulthood. In this review, we describe the role of miR-218 in stress-induced neuropsychiatric conditions with an emphasis on stress-related disorders.

Attentional bias to threat and gray matter volume morphology in high anxious individuals

In a sample of highly anxious individuals, the relationship between gray matter volume brain morphology and attentional bias to threat was assessed. Participants performed a dot-probe task of attentional bias to threat and gray matter volume was acquired from whole brain structural T1-weighted magnetic resonance imaging scans. The results replicate previous findings in unselected samples that elevated attentional bias to threat is linked to greater gray matter volume in the middle frontal gyrus and superior frontal gyrus. In addition, we provide novel evidence that elevated attentional bias to threat is associated with greater gray matter volume in the inferior frontal gyrus, insula, cerebellum, and other distributed regions. Lastly, exploratory analyses provide initial evidence that distinct subregions of the right posterior parietal cortex may contribute to attentional bias in a sex-specific manner. Our results illuminate how differences in gray matter volume morphology relate to attentional bias to threat in anxious individuals. This knowledge could inform neurocognitive models of anxiety-related attentional bias to threat.