Psychiatry and Clinical Neurosciences最新文献

Aim: The current study aims to investigate the association of serum brain-derived neurotrophic factor (BDNF) levels with symptoms of depression in adults with and without prevalent cardiovascular disease (CVD), an often burdensome comorbidity.

Methods: This cross-sectional study included participants from FHS (Framingham Heart Study) who had available serum BDNF levels. Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression Scale (CES-D) with a score ≥16 indicating mild to moderate and ≥21 severe depression. Participants taking antidepressant medications were excluded from the study.

Results: Altogether 3716 FHS participants were included in the final analysis (mean age, 64.3 ± 11.5 years; 55% women). After adjusting for potential confounders, greater BDNF levels were associated with reduced severe depression risk (odds ratio [OR], 0.78 [95% CI, 0.64-0.96]; P = 0.016). Among participants with CVD, greater BDNF levels were related to lower risk of depressive symptoms (CES-D ≥ 16 OR, 0.63 [95% CI, 0.45-0.89], P = 0.008; CES-D ≥ 21 OR, 0.49 [95% CI, 0.31-0.76], P = 0.002). The inverse relationship between BDNF and depressive symptom risk was present in women with CVD (CES-D ≥ 16 OR, 0.63 [95% CI, 0.40-0.99], P = 0.047; CES-D ≥ 21 OR, 0.38 [95% CI, 0.21-0.70], P = 0.002) but not in men.

Conclusion: Lower serum BDNF levels are associated with a higher risk of depressive symptoms in CVD, particularly among women. These findings implicate BDNF in the complex biological mechanisms that underlie prior associations observed between CVD and depression. To reduce the burden of depression in the large proportion of midlife and older adults with CVD, a better understanding of how BDNF may modify these pathways is merited.

Aim: Short tandem repeats (STRs) are repetitive DNA sequences and highly mutable in various human disorders. While the involvement of STRs in various genetic disorders has been extensively studied, their role in autism spectrum disorder (ASD) remains largely unexplored. In this study, we aimed to investigate genetic association of STR expansions with ASD using whole genome sequencing (WGS) and identify risk loci associated with ASD phenotypes.

Methods: We analyzed WGS data of 634 ASD families and performed genome-wide evaluation for 12,929 STR loci. We found rare STR expansions that exceeded normal repeat lengths in autism cases compared to unaffected controls. By integrating single cell RNA and ATAC sequencing datasets of human postmortem brains, we prioritized STR loci in genes specifically expressed in cortical development stages. A deep learning method was used to predict functionality of ASD-associated STR loci.

Results: In ASD cases, rare STR expansions predominantly occurred in early cortical layer-specific genes involved in neurodevelopment, highlighting the cellular specificity of STR-associated genes in ASD risk. Leveraging deep learning prediction models, we demonstrated that these STR expansions disrupted the regulatory activity of enhancers and promoters, suggesting a potential mechanism through which they contribute to ASD pathogenesis. We found that individuals with ASD-associated STR expansions exhibited more severe ASD phenotypes and diminished adaptability compared to non-carriers.

Conclusion: Short tandem repeat expansions in cortical layer-specific genes are associated with ASD and could potentially be a risk genetic factor for ASD. Our study is the first to show evidence of STR expansion associated with ASD in an under-investigated population.

Aim: Adolescents born very preterm (VPT; <32 weeks of gestation) face an elevated risk of executive, behavioral, and socioemotional difficulties. Evidence suggests beneficial effects of mindfulness-based intervention (MBI) on these abilities. This study seeks to investigate the association between the effects of MBI on executive, behavioral, and socioemotional functioning and reliable changes in large-scale brain networks dynamics during rest in VPT young adolescents who completed an 8-week MBI program.

Methods: Neurobehavioral assessments and resting-state functional magnetic resonance imaging were performed before and after MBI in 32 VPT young adolescents. Neurobehavioral abilities in VPT participants were compared with full-term controls. In the VPT group, dynamic functional connectivity was extracted by using the innovation-driven coactivation patterns framework. The reliable change index was used to quantify change after MBI. A multivariate data-driven approach was used to explore associations between MBI-related changes on neurobehavioral measures and temporal brain dynamics.

Results: Compared with term-born controls, VPT adolescents showed reduced executive and socioemotional functioning before MBI. After MBI, a significant improvement was observed for all measures that were previously reduced in the VPT group. The increase in executive functioning, only, was associated with reliable changes in the duration of activation of large-scale brain networks, including frontolimbic, amygdala-hippocampus, dorsolateral prefrontal, and visual networks.

Conclusion: The improvement in executive functioning after an MBI was associated with reliable changes in large-scale brain network dynamics during rest. These changes encompassed frontolimbic, amygdala-hippocampus, dorsolateral prefrontal, and visual networks that are related to different executive processes including self-regulation, attentional control, and attentional awareness of relevant sensory stimuli.

Aim: The gut microbiota can influence human behavior. However, due to the massive multiple-testing problem, research into the relationship between microbiome ecosystems and the human brain faces drawbacks. This problem arises when attempting to correlate thousands of gut bacteria with thousands of brain voxels.

Methods: We performed brain magnetic resonance imaging (MRI) scans on 133 participants and applied machine-learning algorithms (Ridge regressions) combined with permutation tests. Using this approach, we were able to correlate specific gut bacterial families with brain MRI signals, circumventing the difficulties of massive multiple testing while considering sex, age, and body mass index as confounding factors.

Results: The relative abundance (RA) of the Selenomonadaceae, Clostridiaceae, and Veillonellaceae families in the gut was associated with altered cerebellar, visual, and frontal T2-mapping and diffusion tensor imaging measures. Conversely, decreased relative abundance of the Eubacteriaceae family was also linked to T2-mapping values in the cerebellum. Significantly, the brain regions associated with the gut microbiome were also correlated with depressive symptoms and attentional deficits.

Conclusions: Our analytical strategy offers a promising approach for identifying potential brain biomarkers influenced by gut microbiota. By gathering a deeper understanding of the microbiota-brain connection, we can gain insights into the underlying mechanisms and potentially develop targeted interventions to mitigate the detrimental effects of dysbiosis on brain function and mental health.

Aim: Patients with cancer experience various forms of psychological distress, including depressive symptoms, which can impact quality of life, elevate morbidity risk, and increase medical costs. Psychotherapy and pharmacotherapy are effective for reducing depressive symptoms among patients with cancer, but most patients prefer psychotherapy. This study aimed to develop an efficient and effective smartphone psychotherapy component to address depressive symptom.

Methods: This was a decentralized, parallel-group, multicenter, open, individually randomized, fully factorial trial. Patients aged ≥20 years with cancer were randomized by the presence/absence of three cognitive-behavioral therapy (CBT) skills (behavioral activation [BA], assertiveness training [AT], and problem-solving [PS]) on a smartphone app. All participants received psychoeducation (PE). The primary outcome was change in the patient health questionnaire-9 (PHQ-9) total score between baseline and week 8. Secondary outcomes included anxiety.

Results: In total, 359 participants were randomized. Primary outcome data at week 8 were obtained for 355 participants (99%). The week 8 PHQ-9 total score was significantly reduced from baseline for all participants by -1.41 points (95% confidence interval [CI] -1.89, -0.92), but between-group differences in change scores were not significant (BA: -0.04, 95% CI -0.75, 0.67; AT: -0.16, 95% CI -0.87, 0.55; PS: -0.19, 95% CI -0.90, 0.52).

Conclusion: As the presence of any of the three intervention components did not contribute to a significant additive reduction of depressive symptoms, we cannot make evidence-based recommendations regarding the use of specific smartphone psychotherapy.