Biological Psychiatry最新文献

Maternal prenatal depression can affect child brain and behavioral development. Specifically, altered limbic network structure and function is a likely mechanism through which prenatal depression impacts the life-long mental health of exposed children. While developmental trajectories are influenced by many factors that exacerbate risk or promote resiliency, the role of child age and sex in the relationship between prenatal depression and the child brain remains unclear. Here, we review studies of associations between prenatal depression and brain structure and function, with a focus on the role of age and sex in these relationships. After exposure to maternal prenatal depression, altered amygdala, hippocampal, and frontal cortical structure, as well as changes in functional and structural connectivity within the limbic network, are evident during the fetal, infant, preschool, childhood, and adolescent stages of development. Sex appears to play a key role in this relationship, with evidence of differential findings particularly in infants, with males showing smaller and females larger hippocampal and amygdala volumes following prenatal depression. Longitudinal studies in this area have only begun to emerge within the last 5 years and will be key to understanding critical windows of opportunity. Future research focused on the role of age and sex in this relationship is essential to further inform screening, policy, and interventions for children exposed to prenatal depression, interrupt the intergenerational transmission of depression, and ultimately support healthy brain development.

Background: Evidence regarding metabolic alterations associated with maternal antenatal depression (AD) is limited, and their role as potential biomarkers that improve the prediction of AD and adverse childbirth, neurodevelopmental, and mental health outcomes remains unexplored.

Methods: In a cohort of 331 mother-child dyads, we studied associations between AD (a history of medical register diagnoses and/or a Center for Epidemiological Studies Depression Scale score during pregnancy ≥ 20) and 95 metabolic measures analyzed 3 times during pregnancy. We tested whether the AD-related metabolic measures increased variance explained in AD over its risk factors and in childbirth, neurodevelopmental, and mental health outcomes over AD. We replicated the findings in a cohort of 416 mother-child dyads.

Results: Elastic net regression identified 15 metabolic measures that collectively explained 25% (p < .0001) of the variance in AD, including amino and fatty acids, glucose, inflammation, and lipids. These metabolic measures increased the variance explained in AD over its risk factors (32.3%, p < .0001 vs. 12.6%, p = .004) and in child gestational age (9.0%, p < .0001 vs. 0.7%, p = .34), birth weight (9.0%, p = .03 vs. 0.7%, p = .33), developmental milestones at the age of 2.3 to 5.7 years (21.0%, p = .002 vs. 11.6%, p < .001), and any mental or behavioral disorder by the age of 13.1 to 16.8 years (25.2%, p = .03 vs. 5.0%, p = .11) over AD, child sex, and age. These findings were replicated in the independent cohort.

Conclusions: AD was associated with alterations in 15 metabolic measures, which collectively improved the prediction of AD over its risk factors and birth, neurodevelopmental, and mental health outcomes in children over AD. These metabolic measures may become biomarkers that can be used to identify at-risk mothers and children for personalized interventions.

Background: Glutathione (GSH) is a crucial antioxidant in the human brain. Although proton magnetic resonance spectroscopy using the Mescher-Garwood point-resolved spectroscopy sequence is highly recommended, limited literature has measured cortical GSH using this method in major psychiatric disorders.

Methods: By combining magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging, we quantified brain GSH and glutamate in the medial prefrontal cortex and precuneus and explored relationships between GSH levels and intrinsic neuronal activity as well as clinical symptoms among healthy control (HC) participants (n = 30), people with major depressive disorder (MDD) (n = 28), and people with obsessive-compulsive disorder (OCD) (n = 28).

Results: GSH concentrations were lower in the medial prefrontal cortex and precuneus in both the MDD and OCD groups than in the HC group. In the HC group, positive correlations were noted between GSH and glutamate levels and between GSH and fractional amplitude of low-frequency fluctuations in both regions. However, while these correlations were absent in both patient groups, there was a weak positive correlation between glutamate and fractional amplitude of low-frequency fluctuations. Moreover, GSH levels were negatively correlated with depressive and compulsive symptoms in MDD and OCD, respectively.

Conclusions: These findings suggest that reduced GSH levels and an imbalance between GSH and glutamate could increase oxidative stress and alter neurotransmitter signaling, thereby leading to disruptions in GSH-related neurochemical-neuronal coupling and psychopathologies across MDD and OCD. Understanding these mechanisms could provide valuable insights into the processes that underlie these disorders and potentially become a springboard for future directions and advancing our knowledge of their neurobiological foundations.

Background: Brain serotonin 4 receptor (5-HT₄R) levels are lower in untreated patients with major depressive disorder (MDD) and are linked to verbal memory. Here, we investigated the relationship between 5-HT₄R levels, clinical outcomes, and cognitive function in patients with MDD who initiated selective serotonin reuptake inhibitor drug treatment.

Methods: Ninety patients with moderate to severe depression underwent molecular brain imaging to measure 5-HT₄R binding prior to antidepressant treatment with escitalopram. Pretreatment 5-HT₄R binding was assessed for its ability to predict treatment outcome at weeks 4, 8, or 12. In 40 patients who were rescanned 8 weeks posttreatment, change in cerebral 5-HT₄R binding was correlated with change in verbal memory and with change in depressive symptoms, as evaluated by the 6-item Hamilton Depression Rating Scale.

Results: After 8 weeks of serotonergic intervention, neostriatal 5-HT₄R binding was reduced by 9%. Global change in 5-HT₄R binding from baseline was associated with verbal memory outcomes, but not with overall clinical depressive symptom outcomes. Pretreatment 5-HT₄R binding did not predict clinical recovery status at week 8 and was not associated with change in the 6-item Hamilton Depression Rating Scale scores.

Conclusions: In patients with moderate to severe MDD, treatment with selective serotonin reuptake inhibitors downregulated neostriatal 5-HT₄R levels, which is consistent with the notion that the drugs increase cerebral extracellular serotonin. The less global brain 5-HT₄R levels were downregulated after selective serotonin reuptake inhibitors, the more verbal memory improved, highlighting the potential importance of 5-HT₄R as a treatment target in MDD. The findings offer insights into mechanisms that underlie antidepressant effects and point to new directions for precision medicine treatments for MDD.

Background: Insomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure detection of involved brain circuits. In the current study, we investigated whether structural brain connectivity deviations differed between recently discovered and validated insomnia subtypes.

Methods: Structural and diffusion-weighted 3T magnetic resonance imaging data from 4 independent studies were harmonized. The sample consisted of 73 control participants without sleep complaints and 204 participants with insomnia who were grouped into 5 insomnia subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex was used to evaluate group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density, and mean diffusivity and evaluated within 3 different atlases.

Results: Insomnia subtypes showed differentiating profiles of deviating structural connectivity that were concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in 4 of the 5 subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive, and slightly distressed high reactive. Connectivity deviation profile significance ranged from p = .001 to p = .049 for different resolutions of brain parcellation and connectivity weight.

Conclusions: Our results provide an initial indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping insomnia may be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

Background: Abnormalities in structural-functional connectivity (SC-FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms that underlie regional SC-FC coupling patterns are not well understood.

Methods: We enrolled 182 patients with MDD and 157 healthy control participants and quantified the intergroup differences in regional SC-FC coupling. Extreme gradient boosting (XGBoost), support vector machine, and random forest models were constructed to assess the potential of SC-FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC-FC coupling in patients with MDD, neurotransmitter distributions, and gene expression.

Results: We observed increased regional SC-FC coupling in the default mode network (t₃₃₇ = 3.233) and decreased coupling in the frontoparietal network (t₃₃₇ = -3.471) in patients with MDD compared with healthy control participants. XGBoost (area under the receiver operating characteristic curve = 0.853), support vector machine (area under the receiver operating characteristic curve = 0.832), and random forest (p < .05) models exhibited good prediction performance. The alterations in regional SC-FC coupling in patients with MDD were correlated with the distributions of 4 neurotransmitters (p < .05) and expression maps of specific genes. These enriched genes were implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on 2 brain atlases.

Conclusions: This work enhances our understanding of MDD and paves the way for the development of additional targeted therapeutic interventions.

Background: Longitudinal changes in cognitive function may be crucial in predicting clinical outcomes in clinical high risk (CHR) individuals. This study aims to investigate the predictive value of baseline cognitive impairment and short-term cognitive changes for non-remission and conversion to psychosis in individuals at CHR for psychosis, compared with healthy controls (HC).

Methods: This study employed a multiple-group prospective design with a 3-year follow-up. CHR individuals and HCs were assessed at baseline and at a 2-month follow-up. Neuropsychological performance was evaluated using the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery.

Results: The study included 310 CHR individuals and 93 HCs. Significant improvements in predicting non-remission in CHR individuals were observed when incorporating cognitive changes over 2 months (AUC for baseline cognition, 0.690; AUC for changes, 0.819; Z=3.365, p<0.001). Key predictors included the Revised Hopkins Verbal Learning Test (HVLT-R; β=0.083, p=0.003), Wechsler Memory Scale-III spatial span (WMS-3; β=0.330, p<0.001), and Revised Brief Visuospatial Memory Test (BVMT-R; β=0.127, p<0.001). Conversely, predicting conversion to psychosis showed no significant difference between baseline and 2-month cognitive changes (AUC for baseline cognition, 0.667; AUC for changes, 0.666; Z=0.021, p=0.242).

Conclusions: The findings underscore the importance of dynamic cognitive monitoring in CHR individuals. Short-term cognitive changes significantly enhance the prediction of non-remission but do not add predictive value for conversion to psychosis beyond baseline assessments. Specific cognitive domains, such as verbal learning and working memory, are particularly valuable for predicting clinical outcomes.

Chronic social isolation alters behavior across animal species. Genetic model organisms such as mice and flies provide crucial insight into the molecular and physiological effects of social isolation on brain cells and circuits. Here, we comparatively review recent findings regarding the function of conserved neuropeptides on social isolation in mice and flies. Analogous functions of three classes of neuropeptides - tachykinins, cholecystokinins, and neuropeptides Y/F - in the two model organisms, suggest that these molecules may be involved in modulating behavioral changes induced by social isolation across a wider range of species, including humans. Comparative approaches armed with tools to dissect neuropeptidergic function can lead to an integrated understanding of the impacts of social isolation on brain circuits and behavior.

Background: Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants underlying AUD. However, whole-exome sequencing (WES) studies of AUD are hampered by the lack of available samples.

Methods: We analyzed WES data of 4,530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank (UKB), which represents an unprecedented resource for exploring the contribution of coding variants in AUD. After quality controls, 2,039 European-ancestry (EUR: 1,420 cases) and 1,750 African-ancestry samples (AFR: 1,142 cases) from Yale-Penn, and 415,617 EUR samples (12,861‬ cases), 6,142 AFR samples (130 cases) and 4,607 South Asian (SAS) samples (130 cases) from UKB were included in the analyses.

Results: We confirmed the well-known functional variant rs1229984 in ADH1B (P=4.88×10^-31) and several other variants in ADH1C. Gene-based collapsing tests considering the high allelic heterogeneity revealed the previously unreported genes, CNST (P=1.19×10^-6) attributable to rare variants with allele frequency < 0.001, and IFIT5 (P=3.74×10^-6) driven by the burden of both common and rare loss-of-function and missense variants.

Conclusions: This study extends our understanding of the genetic architecture of AUD, by providing insights into the contribution of rare coding variants, separately and convergently with common variants in AUD.

Background: Tourette disorder is characterized by motor hyperactivity and tics that are believed to originate in basal ganglia. Postmortem immunocytochemical analyses previously revealed decreases in cholinergic, parvalbumin, and somatostatin interneurons (IN) within the caudate/putamen of individuals with TS.

Methods: We obtained transcriptome and open chromatin datasets by snRNAseq and snATAC-seq, respectively, from caudate/putamen postmortem specimens of 6 adult TS and 6 matched normal control (NC). Differential gene expression and differential chromatin accessibility analyses were performed in identified cell types.

Results: The data reproduced the known cellular composition of the human striatum, including a majority of medium spiny neurons (MSN) and small populations of GABAergic and cholinergic IN. IN were decreased by ∼50% in TS brains, with no difference in other cell types. Differential gene expression analysis suggested that mitochondrial oxidative metabolism in MSN and synaptic adhesion and function in IN were both decreased in TS subjects, while there was activation of immune response in microglia. Gene expression changes correlated with changes in activity of cis-regulatory elements, suggesting a relationship of transcriptomic and regulatory abnormalities in MSN, OL and AST of TS brains.

Conclusions: This initial analysis of the TS basal ganglia transcriptome at the single cell level confirms the loss and synaptic dysfunction of basal ganglia IN, consistent with in vivo basal ganglia hyperactivity. In parallel, oxidative metabolism was decreased in MSN and correlated with activation of microglia cells, attributable at least in part to dysregulated activity of putative enhancers, implicating altered epigenomic regulation in TS.