Direct changes of neurometabolic concentrations in the pregenual anterior cingulate cortex among obsessive-compulsive patients after repetitive transcranial magnetic stimulation treatment

Efficacy and acceptability of brain stimulation for anxiety disorders, OCD, and PTSD: A systematic review and network meta-analysis of randomized controlled trials

BACKGROUND

The present study aimed to conduct a systematic review and network meta-analysis to investigate the efficacy and acceptability of brain stimulation techniques (BSTs) for anxiety disorders, obsessive-compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).

METHODS

A comprehensive search was performed in Embase, PubMed, Web of Science, PsycINFO, Cochrane, ClinicalTrials.gov and HowNet databases for studies published before September 10, 2023. Randomized clinical trials that involved deep brain stimulation (DBS), electroconvulsive therapy (ECT), repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), sham therapy, or health control were included for analysis. The primary outcome was efficacy, while acceptability was considered as a secondary outcome.

RESULTS

The sample consisted of 1333 patients with various anxiety disorders including social anxiety disorder, general anxiety disorder, panic disorder, social panic, obsessive-compulsive disorder, post-traumatic stress disorder, and agoraphobia, recruited from 41 trials with 86 treatment arms. Network meta-analysis showed that some BSTs had higher efficacy compared to controls, including DBS, ECT, cathodal tDCS, high-frequency rTMS (hf-rTMS), anodal tDCS, and low-frequency rTMS (lf-rTMS). Furthermore, hf-rTMS, lf-rTMS, and ECT had high acceptability in terms of odds ratio (OR).

LIMITATIONS

This study has limitations, including a focus on specific types of brain stimulation for anxiety disorders, OCD and PTSD and not considering factors like stimulation parameters. Future research should explore a broader range of technologies and parameters across various psychiatric and neurological conditions.

CONCLUSION

The study results suggest that BSTs are effective treatments for anxiety disorders, OCD and PTSD; lf-rTMS may be considered as the most promising option.

EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder

BACKGROUND

Microstate characterization of electroencephalogram (EEG) is a data-driven approach to explore the functional changes and interrelationships of multiple brain networks on a millisecond scale. This study aimed to explore the pathological changes of whole-brain functional networks in patients with obsessive-compulsive disorders (OCD) through microstate analysis and further to explore its potential value as an auxiliary diagnostic index.

METHODS

Forty-eight OCD patients (33 with more than moderate anxiety symptoms, 15 with mild anxiety symptoms) and 52 healthy controls (HCs) were recruited. Brain activities during eyes-closed period were collected using 64-channel electroencephalography. The differences in microstate features between OCD patients and HCs were compared, and the relationship between the microstate features and clinical symptoms were explored. Key microstate features were selected for machine learning modeling to achieve targeted classifications.

RESULTS

The probability of transition from microstate B to C was significantly lower in OCD patients compared to HCs, and the obsessive thoughts factor scores were significantly correlated with the duration of microstate A, the occurrence of microstate B, and the transition probability from microstate C to B. The occurrence rate of microstate C was significantly negatively correlated with the Hamilton rating scale for anxiety (HAMA) scores. The AUC (Area Under the Receiver Operating Characteristic Curve) of the machine learning model in the test set classification between the above two groups and between OCD patients with more than moderate/mild anxiety symptoms could achieve 70.43% and 77.13%, respectively.

CONCLUSION

EEG microstate characteristics were altered in OCD patients, and these changes were closely associated with obsessive thoughts and anxiety symptoms. Besides, the machine learning classification model based on microstate features has limited ability to identify OCD, and further optimization on this classification approach is still needed in the future.

Reduced sleep quality defines a subtype of obsessive-compulsive disorder with lower Glx levels in the resting thalamus and worse response inhibition

BACKGROUND

The aim of this study was to investigate the differences between resting and active thalamic neurometabolite levels and inhibitory function in obsessive compulsive disorder (OCD) patients with poor sleep quality (PSQ was defined as Pittsburgh Sleep Quality Index >5 and sleep efficiency ≤85%) compared to OCD patients with good sleep quality (GSQ) and healthy controls (HCs), as well as the relationship of these indices to obsessive compulsive symptoms.

METHODS

Functional magnetic resonance spectroscopy (fMRS) was used to measure resting and active thalamic neurometabolite levels in 72 subjects (20 HCs and 38 OCD patients included in study analysis). Response inhibition function was measured by the Go-Nogo task before and during MRS recording. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The symptoms of OCD, anxiety and depression were evaluated using relevant clinical scales.

RESULTS

OCD patients exhibited significantly reduced Glx/Cr levels in the resting thalamus. The levels of resting thalamic Glu/Cr and Glx/Cr in OCD patients with PSQ were significantly lowest. OCD patients had significantly lower correct rates on Go tasks, higher error rates on Nogo tasks, and longer error average response times (EART) to the Nogo task. OCD patients with PSQ demonstrated the highest Nogo task error rate and the longest EART to Nogo task. Furthermore, PSQI scores exhibited negative correlations with Glu/Cr and Glx/Cr in the resting thalamus.

CONCLUSION

OCD patients with PSQ demonstrated reduced levels of thalamic resting Glx and more pronounced response inhibitory function impairment. Aberrant neurometabolite levels in critical brain regions, coupled with heightened response inhibition function deficits, may be a neurobiological basis for the PSQ that OCD patients generally exhibit.