Translational Psychiatry最新文献

Bumetanide, a specific NKCC1 co-transporter inhibitor, restores deficient GABAergic inhibition implicated in various brain disorders, including Autism Spectrum Disorders (ASD). In keeping with this mechanism, nine successful phase 2 clinical trials, conducted by seven independent teams using an identical protocol, have shown significant improvements in ASD symptoms among individuals treated with Bumetanide. Despite these promising results, two large phase 3 clinical trials (over 400 children recruited in approximately 50 centers and covering age groups 2-6 and 7-17 years) failed with no significant difference between patients treated by placebo or Bumetanide. This failure may stem from the substantial heterogeneity of ASD symptom profiles across the study population, potentially diluting the overall observed treatment effect. To address this, we reanalyzed the phase 3 data using Q-Finder, a supervised machine learning algorithm, aiming to identify subgroups of patients who responded to the treatment. This analysis was based on clinical parameters collected at the baseline of trial and used the same standard endpoints and success criteria defined in the original phase 3 protocol. It enabled the identification of responder subgroups showing a statistically significant difference between placebo and Bumetanide treatment arms. We report detailed descriptions and statistical evaluations of these subgroups. The discovered responder subgroups, representing up to 40% of participants, were cross validated between the two study populations. These findings suggest that meaningful treatment responses can be uncovered within negative phase 3 trials, highlighting the limitations of a one-size-fits-all approach for heterogeneous conditions such as ASD. Machine learning appears to be a promising tool to support this precision medicine strategy.

Selective serotonin reuptake inhibitors (SSRIs) are widely prescribed antidepressants, though their mechanisms of action beyond serotonin transporter (SERT) blockade remain unclear [1]. As previous work on BOLD signal changes remain equivocal, pharmacological multimodal neuroimaging of energy demands and blood flow (CBF) holds promise due to increased specificity of these signals. This may advance the understanding of the involved pharmacodynamic mechanisms and guide treatment strategies of highly prevalent neuropsychiatric disorders. We combine new techniques of functional positron emission tomography (fPET) with high temporal resolution (3 seconds) using [¹⁸F]FDG and simultaneously acquired pseudo-continuous arterial spin labelling (pcASL). Thus, we aimed for a highly quantitative assessment of changes in brain activation following an intravenous SSRI challenge using a randomized, placebo-controlled, double-blind study design. We demonstrate acute drug induced changes in glucose metabolism (K_i) in serotonergic projections, i.e. the striatum and the occipital cortex in 16 healthy volunteers (7 females). In an exploratory analysis, acute effects were observed in the dorsal raphe nucleus. We did not observe corresponding changes in CBF, which suggests that observed SSRI effects are specific to brain energy demands. Our results complement the existing literature on the acute pharmacological effects of SSRIs by providing insights in specific aspects of neuronal activation. Moreover, our findings expand upon the results of existing BOLD fMRI studies and, thus, support the application of this pharmacological neuroimaging protocol in psychopharmacological research.

There is a connection between neuroinflammation and panic attacks (PA), as microglia-driven pro-inflammatory responses help detect homeostatic disturbances like CO₂ inhalation. This model has become widely used in research since CO₂ exposure can trigger PA in humans and panic-related behavior in mice. Minocycline inhibits microglia activation, serving as a promising tool to attenuate CO₂-induced PA. The locus coeruleus (LC) is a CO₂/pH-sensitive region, and disruptions in its activity are linked to psychiatric conditions such as panic disorder (PD). We investigated the involvement of microglia in the respiratory and behavioral responses induced by CO₂ in mice and the effect of minocycline and clonazepam treatment. We also assessed in mice whether LC microglia are activated after hypercapnia using IBA-1 immunohistochemistry. Translationally, PD patients were treated with minocycline and clonazepam and examined for their CO₂-responsiveness. LC microglia were activated 6 h after exposure to 20% CO₂ in mice. This panicogenic stimulus also induced hyperventilation as well as active panic-related escape responses, characterized by jumps and running episodes. Minocycline and clonazepam decreased escape expression during the CO₂ challenge, but only the former drug reduced hyperventilatory responses. None of the drugs changed IL levels in LC. In humans, minocycline reduced the severity of CO₂-induced panic attacks and also modulated the immune response by lowering IL-2sRα and increasing IL-10 levels. Exposure to hypercapnia activates microglia in the LC of mice. Treatment with minocycline, similar to the clinically effective panicolytic clonazepam, attenuates CO₂-induced panic-like responses in both mice and humans. These results support the potential of minocycline as a therapeutic strategy for PD.

Depression and dementia commonly co-occur, yet little is known about depression trajectories across dementia stages. We aimed to map depression occurrence before, during, and after dementia diagnosis, and to identify factors associated with depression among individuals with dementia. This study included 10,051 participants from the Swedish Twin Registry. Participants with incident dementia (n = 2677) were matched with up to 3 controls (n = 7374) by birth year and sex. Depression and dementia diagnoses and their dates were ascertained based on medical records from the National Patient Registry. Conditional Poisson regression estimated incidence rate ratios for depression, while generalized estimating equations examined odds ratios for factors associated with depression. Compared with controls, depression risk among participants with dementia began to increase 6 years pre-diagnosis (incidence rate ratio [95% confidence interval] 2.32 [1.24-4.35]) and peaked during the year of dementia diagnosis (10.38 [7.33-14.69]). Depression risk remained elevated but gradually declined over the following 4 years (3.10 [1.67-5.77]). Female sex (odds ratio 2.21 [1.63-2.99]), smoking (1.58 [1.20-2.08]), heavy drinking (1.88 [1.10-3.21]), and stroke (1.94 [1.31-2.88]) were associated with higher odds of depression before dementia diagnosis, whereas being single (1.71 [1.10-2.37]) and having a history of cancer (1.35 [1.05-1.79]) were associated with post-diagnosis depression. Overall, these findings indicate that depression risk rises before, peaks at, and remains elevated after dementia diagnosis, with specific demographic (sex, marital status) and health-related factors (smoking, alcohol use, stroke, cancer) contributing to its occurrence among individuals with dementia.

Nonsuicidal self-injury (NSSI) in youth is clinically heterogeneous. We aimed to identify distinct psychopathology-based profiles among children and adolescents reporting NSSI and their longitudinal correlates. Participants (N = 1 345) were drawn from the Brazilian High-Risk Cohort Study, which conducted extensive phenotypic assessments at baseline (ages 6-14 years) and across two follow-up waves (ages 9-18 and 13-23 years). First, we applied unsupervised machine-learning algorithms (Self-Organizing Maps and k-means clustering) to identify distinct psychopathology-based profiles among youth reporting NSSI at the second follow-up. We then employed three models to identify longitudinal predictors of these profiles: logistic regression, elastic net, and random forest. Analyses revealed two distinct profiles of youth reporting NSSI, characterized by high and low psychopathology. The high psychopathology profile (n = 117) was associated with factors identifiable earlier in life and characterized by persistent psychiatric symptoms and significant social adversity throughout development (e.g., family problems and bullying). The low psychopathology profile (n = 127) was marked by lower overall psychopathology and experienced mental health problems only later in development, with less severe challenges over time, such as school suspension and milder depressive symptoms. While the logistic regression did not provide overall significant performance, the elastic net (AUC = 0.72 95% CI 0.65-0.77) and random forest (AUC = 0.73 95% CI 0.67-0.78) did. The present study identified two distinct psychopathology-based profiles among youth reporting NSSI and their longitudinal correlates, using machine learning approaches. Early identification of youth in higher-risk profiles can inform early intervention strategies.

Schizophrenia is a severe psychiatric disorder that affects approximately 1% of the population. Despite the availability of antipsychotic therapies, about 30% of patients develop treatment-resistant schizophrenia (TRS), defined by a lack of response to at least two different antipsychotic trials. Although several genetic and environmental factors have been proposed to explain treatment resistance, metabolomic studies investigating circulating metabolites in TRS remain limited. In this pilot cross-sectional study, we conducted untargeted ¹H NMR-based metabolomics to profile serum metabolites in TRS versus non-TRS patients. Notably, multivariate analysis revealed distinct serum metabolome profiles between the two groups. Additionally, Variable Importance in Projection (VIP) analysis and robust volcano plots showed significant differences between TRS versus non-TRS patients in metabolites involved in lipid and amino acid metabolism. Specifically, serine and glycine emerged as key discriminating molecules, prompting a complementary targeted HPLC analysis in the same serum samples. Although no significant group differences were observed in L-serine, D-serine, the D-serine/total serine ratio, or glycine levels, we found a positive correlation between D-serine levels and cognitive performance, particularly in the area of executive function, across the entire patient cohort. Additionally, a significant correlation between glycine and disorganization symptoms was found selectively in TRS patients. In conclusion, our study offers new insights into potential biomarkers for TRS, highlighting serine-glycine pathway as a possible crossroad between systemic dysmetabolism, NMDA receptor dysfunction, and cognitive impairment in TRS.

The neuronal ceroid lipofuscinosis family of lysosomal storage diseases, also called CLN1 disease, is characterized by the deficiency of palmitoyl-protein thioesterase 1 (PPT1). In this study, we investigated the impact of PPT1 deficiency on hippocampal GABAergic interneurons (INs) and associated neural network oscillations in a PPT1-KI (CLN1 c.451 C > T (p.R151X)) mouse model. Using a combination of in vivo electrophysiology, immunostaining, and fiber photometry, we observed that PPT1 deficiency led to the activation of caspase 3 in parvalbumin-positive (PV⁺) INs, an increased activity of pyramidal neurons and theta/gamma oscillation power, and the disruption of theta-gamma cross-frequency coupling (CFC) in the early stage of the CLN1 disease model. In the late stage of the CLN1 disease model, we observed the reduced neuronal activity, extensive neuronal loss including PV⁺ INs, and the emergence of spontaneous epileptiform discharges and the pathological ripples. Treatment with diazepam partially restored oscillatory coupling and reduced seizure-like activities. Our research indicated that PPT1 deficiency leads to early selective impairment of PV⁺ INs, triggering overactivation of pyramidal neurons and network dysfunction, which consequently results in seizures and neurodegeneration. This research provides novel insights into the pathogenesis of CLN1 disease and potential therapeutic strategies for the intervention of CLN1 disease by improving the function of inhibitory INs via caspase inhibition.

Postpartum depression (PPD) is linked to neuroimmune dysregulation. Brexanolone, an intravenous formulation of the neurosteroid allopregnanolone and the first FDA-approved treatment for PPD, produces rapid and sustained antidepressant effects. However, its long-term mechanisms of action remain unclear. This study evaluated brexanolone's prolonged impact on two groups of biomarkers in whole blood: inflammatory mediators and growth/differentiation/neurotrophic factors. Whole blood was also maintained in culture (4 h) and subjected to lipopolysaccharide (LPS) stimulation of the TLR4 inflammatory pathway. Ten individuals with moderate-to-severe PPD received brexanolone and were assessed before, and at 6 h, ~7, and ~30 days post-infusion. BDNF significantly increased and remained elevated through 30 days, representing a sustained neurotrophic response. In contrast, inflammatory mediators CCL11, IL-6, TNF-α, and IL-18 showed rapid reductions by 6 h. TNF-α suppression lasted up to 7 days, while CCL11 and IL-6 remained suppressed through 30 days. These changes were associated with reductions in Hamilton Depression Rating Scale (HAM-D) scores over time. LPS-stimulated whole blood cultures revealed suppression of TLR4-induced CCL11, IL-1β, IL-6, IL-8, IL-18, TNF-α, HMGB1, and MIP-1β at 6 h. IL-8, IL-18, and TNF-α remained suppressed through 7 days, while IL-1β and CCL11 remained suppressed through 30 days, aligning with sustained HAM-D score improvements. Biomarker × time interactions suggested dynamic regulation of inflammatory and neurotrophic pathways. Given the small sample size, these findings should be interpreted as a pilot study, but they indicate that brexanolone promotes both rapid and sustained anti-inflammatory and neurotrophic effects supporting lasting symptom remission in PPD.

Cognitive deficits are a hallmark of Alzheimer's disease (AD), and effective treatments remain elusive. Transcranial alternating current stimulation (tACS), a non-invasive technique, has shown potential in improving cognitive function across various populations, but further research is needed to investigate its efficacy in AD. In a randomized, double-blind, sham-controlled pilot trial, 36 mild AD patients received active or sham theta-tACS (8 Hz, 1.6 mA, 20-min daily) during n-back task for two weeks, followed by a 10-week follow-up. Cognitive assessments and resting-state EEG were analyzed at baseline, after-treatment, and follow-up. The results showed that the active group demonstrated significant cognitive improvements after treatment (MMSE: t (15) =-3.273, p = 0.005, Cohen's d = 0.82), particularly in short-term memory (MMSE-recall: Z = -2.11, p = 0.035, r = 0.53), with maintained benefits after 10 weeks. In contrast, the sham group exhibited long-term cognitive decline (MMSE: t (4) = 3.586, p = 0.023, Cohen's d = -1.60). EEG analysis revealed reduced gamma power (t (23) = 2.689, p = 0.013, Cohen's d = 1.077) and theta connectivity in active group, particularly in the frontotemporal regions (F4/F7: t (23) = 2.467, p = 0.021, Cohen's d = 0.988; F4/T3: t (23) = 2.465, p = 0.022, Cohen's d = 0.987), which was correlated with cognitive improvements (R = -0.57, p = 0.043). In conclusion, tACS combining cognitive training may offer cognitive benefits in mild AD by modulating neural activity, though further studies are needed to clarify its mechanisms.