European Archives of Psychiatry and Clinical Neuroscience最新文献

Background: Mental disorders are a major and evolving contributor to morbidity among women of child-bearing age (WCBA). However, long-term trends, geographic inequalities, and the future burden in this population remain incompletely characterised. We quantified the burden of mental disorders among WCBA (15-49 years) from 1990 to 2021 and projected trends to 2050.

Methods: We assessed the burden of 10 mental disorder categories among WCBA aged 15-49 years in 204 countries and territories using GBD 2021, including 9 specified mental disorders and a residual category ("other mental disorders"). We analysed prevalence and disability-adjusted life-years (DALYs) as numbers and age-standardised rates (ASPR and ASDR). A Bayesian age-period-cohort model was used to generate projections through 2050.

Results: Overall, ASPR and ASDR declined from 1990 to 2019; compared with the pre-pandemic baseline in 2019, both indicators were higher in 2020-2021. Age-specific prevalence generally increased with age and peaked at 40-44 years, although patterns differed by disorder category. At the national level, Greenland and Portugal had the highest ASPR and ASDR, whereas Vietnam had the lowest prevalence and North Korea had the lowest DALYs. Across the 21 GBD regions, higher SDI was associated with higher ASPR and ASDR, with marked regional heterogeneity. Projections suggested that the burden of mental disorders among WCBA will increase through 2050, largely driven by anxiety and depressive disorders.

Conclusions: The burden of mental disorders among WCBA remains substantial and is projected to rise through 2050, with increases during 2020-2021 relative to the 2019 baseline. These findings underscore the need for context-specific strategies that strengthen surveillance and expand accessible prevention and care-particularly for anxiety and depressive disorders-across diverse sociodemographic settings.

Background: Sleep traits have been linked to cognitive aging, but observational associations are susceptible to confounding and reverse causation. Using genetically informed polygenic risk scores (PRSs), this study examined associations between genetic liability to sleep traits and cognitive function in an East Asian population. We further assessed whether educational attainment, as a marker of cognitive reserve, modifies these associations.

Methods: Participants aged ≥ 60 years from the Taiwan Biobank underwent cognitive assessment using the Mini-Mental State Examination (MMSE) at baseline (n = 27,343) and follow-up (n = 6,273; mean follow-up = 3.9 years). PRSs for chronotype, sleep duration, long sleep, short sleep, insomnia, and daytime napping were constructed. Associations with baseline MMSE and longitudinal MMSE change were evaluated, and PRS × education interactions were tested.

Results: Higher PRSs for early chronotype, longer sleep duration, and long sleep (> 8 h) were associated with lower baseline MMSE scores (β range per SD increase: -0.05 to - 0.03), but were not associated with MMSE change over follow-up. A significant interaction was observed between long-sleep PRS and education for MMSE change (p for interaction = 0.0008), with greater decline among individuals with lower educational attainment. In contrast, no association was observed in higher-education groups.

Conclusions: Genetic liability to early chronotype and long sleep duration is associated with lower late-life cognitive performance, primarily reflecting differences in baseline cognitive status rather than short-term cognitive decline. Higher educational attainment may mitigate cognitive vulnerability associated with genetic predisposition to long sleep, consistent with a cognitive-reserve framework.

Purpose: Childhood-onset asthma is associated with an increased risk of severe mental illnesses later in life. However, the causal relationship between childhood-onset asthma and major mental disorders remains unclear.

Methods: A two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal effects of childhood-onset asthma (n = 327,670) on six major mental illnesses, including major depressive disorder (n = 143,265), bipolar disorder (n = 353,899), schizophrenia (n = 130,644), anxiety (n = 10,240), autism (n = 46,350), and ADHD (n = 225,534), using summary statistics of genome-wide association studies (GWAS). The inverse variance weighted (IVW) method, along with the weighted median and the MR-Egger method, was employed to obtain causal estimates. Multiple sensitivity analyses were conducted to examine the robustness of the estimates. Additionally, the direct effects of childhood-onset asthma on mental disorders after accounting for the effects of adult-onset asthma were evaluated through the multivariable MR (MVMR) analysis. To eliminate potential reverse causality, a reverse MR analysis was conducted, treating mental disorders as the exposure and childhood-onset asthma as the outcome.

Results: Genetically determined, childhood-onset asthma was significantly associated with an increased risk of depression (IVW OR = 1.059, 95% CI: 1.025-1.095, p = 5.72e-04) and bipolar disorder (IVW OR = 1.065, 95% CI: 1.027- 0.105, p = 6.75e-04). However, it was not associated with other mental disorders. Further MVMR analysis indicated that the causal relationships remained significant after accounting for adult-onset asthma. Interestingly, childhood- and adult-onset asthma exerted distinct causal effects on depression and bipolar disorder. Reverse MR analysis revealed no causal relationships between the six assessed mental disorders and either childhood-onset asthma or the age of asthma onset.

Conclusions: The MR analysis revealed a significant causal relationship between genetically determined, childhood-onset asthma and an elevated risk of depression and bipolar disorder later in life. The causal effects of childhood-onset asthma were distinct from those of adult-onset asthma. Further studies are warranted to investigate the underlying mechanisms of these causal relationships.

Brain-derived neurotrophic factor (BDNF) is crucial for the growth, differentiation and maintenance of neuronal systems, which is closely associated with major depressive disorder (MDD). The objective of this study was to investigate the BDNF levels and their associations with psychopathology and lipid metabolism parameters in adolescents with MDD. From January to December 2021, the study included 141 adolescents with MDD and 90 healthy controls (HCs). The Center for Epidemiological Studies Depression Scale (CES-D), the Insomnia Severity Index Scale (ISI), the Epworth Sleepiness Scale (ESS) and the Positive and Negative Suicidal Ideation Scale (PANSI) were used to assess depressive symptoms, insomnia, excessive daytime sleepiness, and suicidal ideation, respectively. BDNF levels and lipid metabolism parameters were also measured. Compared to HCs, adolescents with MDD had significantly lower BDNF levels (p < 0.001). In patients, BDNF levels were positively correlated with age, BMI, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C); and negatively correlated with the scores of CES-D and ISI (all p < 0.05). The results of the multivariate linear regression analyses indicated that BDNF levels were positively associated with age (β = 0.198, t = 2.447, p = 0.016), first-episode MDD (β = 0.176, t = 2.234, p = 0.027) and TC level (β = 0.240, t = 3.048, p = 0.003), and negatively associated with the scores of ESS (β = -0.171, t = -2.203, p = 0.029) and ISI (β = -0.231, t = -2.996, p = 0.003). Of note, the associations between BDNF and psychopathology were observed only in female and first-episode patients. BDNF levels were decreased in adolescents with MDD. Patients with low BDNF levels were in a more severe psychiatric state and had changes in lipid metabolism parameters. This study provided preliminary evidence that BDNF may play a role in the onset and progression of MDD.

Background: High dosage accelerated intermittent theta-burst stimulation (aiTBS) protocols (10 sessions per day for 5 days) combined with precision targeting and depth adjusted iTBS intensity yield high response and remission rates in depression. However, disentangling their efficacy components to develop pragmatic mental health solutions is challenging. This pilot study applied such a high dosage aiTBS protocol without using any precision features.

Methods: Eight patients with treatment-resistant depression (TRD) underwent open-label aiTBS targeting the left dorsolateral prefrontal cortex (DLPFC) using the Beam F3 algorithm. Over 5 days, patients received 50 aiTBS sessions, each delivering 1800 pulses at 90% resting motor threshold with 50-min inter-session intervals. All patients underwent a 4 weeks follow-up without stimulation, were offered tDCS for 4 weeks thereafter and had a final follow-up after 6 months. Treatment effects were assessed by clinical and cognitive measures.

Results: Patients received 46 aiTBS sessions on average. At one-month follow-up, mean MADRS scores decreased by -12.50 ± 9.81 (Cohen's d = 2.83; 95% CI, 2.34-3.32; p < 0.001), with response and remission rates of 50% and 12.5%, respectively. After tDCS, 28.6% and 14.3% sustained response and remission, which declined to 16.7% and 0% at six months.

Conclusion: This pilot trial evidenced the antidepressant effect of a high dosage aiTBS protocol comparable with the Stanford Neuromodulation Therapy (SNT) approach but without individualized precision components. Its effectiveness appeared lower than previously reported for SNT. Randomized controlled trials should systematically investigate the contribution of precision components to the overall effectiveness of aiTBS in depression. This trial is a part of a real-world clinical study of non-invasive brain stimulation treatments conducted at our department (preregistered at DRKS-ID: DRKS00024776, drks.de).