Psychiatry and Clinical Neurosciences最新文献

Aim: This study aimed to explore the relationships between serum cortisol levels, personality traits, and the development of Post-Traumatic Stress Disorder (PTSD) over 2 years among individuals with physical injuries.

Methods: Participants were consecutively recruited from a trauma center and followed prospectively for 2 years. At baseline, serum cortisol levels were measured, and personality traits were categorized into five dimensions (Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness), using the Big Five Inventory-10. The diagnosis of PTSD during follow-up (at 3, 6, 12, and 24 months post-injury) was determined using the Clinician-Administered PTSD Scale for DSM-5. Binary and multinomial logistic regression analyses were conducted to examine the interactions between cortisol levels, personality traits, and PTSD development.

Results: Among 923 patients analyzed, 112 (12.1%) were diagnosed with PTSD at some point during the study period, with prevalence rates decreasing from 8.8% at 3 months to 3.7% at 24 months post-injury. Direct associations between cortisol levels or personality traits and PTSD were not observed. However, a significant interaction between lower cortisol levels and higher Neuroticism in relation to PTSD risk was identified, especially during the early follow-up periods (3 to 6 months), but this association waned from the 12-month follow-up onward.

Conclusion: Our findings reveal Neuroticism-dependent associations between serum cortisol levels and PTSD development, exhibiting temporal variations. These results suggest that PTSD development may be influenced by a complex, time-sensitive interplay of biological and psychosocial factors, underscoring the importance of considering individual differences in stress reactivity and personality in PTSD research and treatment.

Neuroimaging databases for neuro-psychiatric disorders enable researchers to implement data-driven research approaches by providing access to rich data that can be used to study disease, build and validate machine learning models, and even redefine disease spectra. The importance of sharing large, multi-center, multi-disorder databases has gradually been recognized in order to truly translate brain imaging knowledge into real-world clinical practice. Here, we review MRI databases that share data globally to serve multiple psychiatric or neurological disorders. We found 42 datasets consisting of 23,293 samples from patients with psychiatry and neurological disorders and healthy controls; 1245 samples from mood disorders (major depressive disorder and bipolar disorder), 2015 samples from developmental disorders (autism spectrum disorder, attention-deficit hyperactivity disorder), 675 samples from schizophrenia, 1194 samples from Parkinson's disease, 5865 samples from dementia (including Alzheimer's disease), We recognize that large, multi-center databases should include governance processes that allow data to be shared across national boundaries. Addressing technical and regulatory issues of existing databases can lead to better design and implementation and improve data access for the research community. The current trend toward the development of shareable MRI databases will contribute to a better understanding of the pathophysiology, diagnosis and assessment, and development of early interventions for neuropsychiatric disorders.

Aims: Schizophrenia, a debilitating mental disorder, is characterized by persistent negative symptoms such as avolition and anhedonia. Currently, there are no effective treatments available for these symptoms. Thus, our study aims to assess the efficacy of online high-definition transcranial direct current stimulation (online HD-tDCS) in addressing the negative symptoms of schizophrenia, utilizing a double-blind, randomized, sham-controlled trial design.

Methods: Fifty-nine patients with schizophrenia were randomized to receive either active HD-tDCS or sham stimulation, targeting the left dorsolateral prefrontal cortex. Outcomes were measured by changes in the Positive and Negative Syndrome Scale Factor Score for Negative Symptom (PANSS-FSNS). Exact low-resolution electromagnetic tomography was used to assess the functional connectivity.

Results: All 59 participants, including 50.84% females with an average age of 43.36 years, completed the trial. In the intention-to-treat analysis, patients receiving active HD-tDCS showed greater improvement in PANSS-FSNS scores compared to those receiving the sham procedure. The differences were 2.34 (95% confidence interval [CI], 1.28-3.40), 4.28 (95% CI, 2.93-5.62), and 4.91 (95% CI, 3.29-6.52) after the intervention, as well as at 1-week and 1-month follow-ups, respectively. A tingling sensation on the scalp was more common in the active group (63.3%) compared to the sham group (10.3%). Additionally, HD-tDCS was associated with a decrease in delta-band connectivity within the default mode network.

Conclusions: High-definition transcranial direct current stimulation was effective and safe in ameliorating negative symptoms in patients with schizophrenia when combined with online functional targeting.

Aim: Neuroinflammation is an important causal factor for a variety of psychiatric disorders. We previously reported increased cerebrospinal fluid interleukin-6 levels in patients with schizophrenia and major depressive disorder. The present study aimed to examine the possible association of interleukin-6 levels with anxiety and frustration, negative valence symptoms shared in various psychiatric disorders.

Methods: We included 129 patients with psychiatric disorders and 70 controls. CSF and plasma interleukin-6 levels were measured by immunoassay kits, and psychological symptoms were assessed with the State-Trait Anxiety Inventory, and the Basic Psychological Need Satisfaction and Frustration Scale. To examine regional cerebral blood flow, patients underwent arterial spin labeling analysis using magnetic resonance imaging.

Results: Cerebrospinal fluid interleukin-6 levels were significantly correlated with State-Trait Anxiety Inventory-trait anxiety (r = 0.25, P = 0.046) and Basic Psychological Need Satisfaction and Frustration Scale-autonomy frustration scores (r = 0.29, P = 0.018). Patients with abnormally high cerebrospinal fluid interleukin-6 levels (defined >97.5 percentile of the controls) had higher scores for trait anxiety (P = 0.035) and autonomy frustration (P = 0.026), and significantly increased regional cerebral blood flow in the left superior temporal gyrus, bilateral nucleus accumbens, and cerebellum than the remaining patients.

Conclusion: Patients with elevated cerebrospinal fluid interleukin-6 constitute a subpopulation of psychiatric disorders associated with anxiety and autonomy frustration, which may be related to altered functions in specific brain areas.

Aims: Anxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders.

Methods: We included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders.

Results: Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k-11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MD $\left(n=47\right)$ , BIP $\left(n=33\right)$ , SCZ $\left(n=71\right)$ , ADHD $\left(n=20\right)$ , and ASD $\left(n=5\right)$ . Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci.

Conclusions: Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.