Molecular Psychiatry最新文献

Weighing risks and benefits of the use of psychotropic medications during pregnancy remains a challenge worldwide. We systematically assessed the strength of associations between psychotropic medication use in pregnant people with mental disorders and various adverse health outcomes in both pregnant people and foetuses. Systematic reviews with meta-analyses of observational studies investigating the association between exposure to psychotropic medication in pregnancy and any adverse health outcomes were included. Credibility was graded into convincing, highly suggestive, suggestive, weak or not significant. Quality of the meta-analyses and of individual studies were assessed with A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) the Newcastle-Ottawa Scale (NOS), respectively. We considered 21 meta-analyses encompassing 17,290,755 participants (AMSTAR 2 high = 1, low = 12, or critically low = 8). Evidence was suggestive for: (1) preterm birth in pregnant people with either any mental disorder (equivalent odds ratio 1.62 (95% confidence interval 1.24–2.12) or depression (1.65 [1.34–2.02]) receiving antidepressants during any trimester of pregnancy; (2) small for gestational age for pregnant people with depression receiving a SSRI during any trimester of pregnancy (1.50 [1.19–1.90]); and (3) major congenital malformation (1.24 [1.09–1.40]) or cardiac malformations (1.28 [1.11–1.47]) in babies for pregnant people with depression or anxiety receiving paroxetine during first trimester of pregnancy. Additional associations were supported by weak evidence, or were not statistically significant. This umbrella review found no convincing or highly suggestive level of evidence of adverse health outcomes associated with psychotropic medication use in pregnant people with mental disorders.

The psychosis spectrum encompasses a heterogeneous range of clinical conditions associated with abnormal brain development. Detecting patterns of atypical neuroanatomical maturation across psychiatric disorders requires an interpretable metric standardized by age-, sex- and site-effect. The molecular and micro-architectural attributes that account for these deviations in brain structure from typical neurodevelopment are still unknown. Here, we aggregate structural magnetic resonance imaging data from 38,696 healthy controls (HC) and 1256 psychosis-related conditions, including first-degree relatives of schizophrenia (SCZ) and schizoaffective disorder (SAD) patients (n = 160), individuals who had psychotic experiences (n = 157), patients who experienced a first episode of psychosis (FEP, n = 352), and individuals with chronic SCZ or SAD (n = 587). Using a normative modeling approach, we generated centile scores for cortical gray matter (GM) phenotypes, identifying deviations in regional volumes below the expected trajectory for all conditions, with a greater impact on the clinically diagnosed ones, FEP and chronic. Additionally, we mapped 46 neurobiological features from healthy individuals (including neurotransmitters, cell types, layer thickness, microstructure, cortical expansion, and metabolism) to these abnormal centiles using a multivariate approach. Results revealed that neurobiological features were highly co-localized with centile deviations, where metabolism (e.g., cerebral metabolic rate of oxygen (CMRGlu) and cerebral blood flow (CBF)) and neurotransmitter concentrations (e.g., serotonin (5-HT) and acetylcholine (α₄β₂) receptors) showed the most consistent spatial overlap with abnormal GM trajectories. Taken together these findings shed light on the vulnerability factors that may underlie atypical brain maturation during different stages of psychosis.

Psychedelics have recently attracted significant attention for their potential to mitigate symptoms associated with various psychiatric disorders. However, the precise neurobiological mechanisms responsible for these effects remain incompletely understood. A valuable approach to gaining insights into the specific mechanisms of action involves comparing psychedelics with substances that have partially overlapping neurophysiological effects, i.e., modulating the same neurotransmitter systems. Imaging data were obtained from the clinical trial NCT03019822, which explored the acute effects of lysergic acid diethylamide (LSD), d-amphetamine, and 3,4-methylenedioxymethamphetamine (MDMA) in 28 healthy volunteers. The clinical trial employed a double-blind, placebo-controlled, crossover design. Herein, various resting-state connectivity measures were examined, including within-network connectivity (integrity), between-network connectivity (segregation), seed-based connectivity of resting-state networks, and global connectivity. Differences between placebo and the active conditions were assessed using repeated-measures ANOVA, followed by post-hoc pairwise t-tests. Changes in voxel-wise seed-based connectivity were correlated with serotonin 2 A receptor density maps. Compared to placebo, all substances reduced integrity in several networks, indicating both common and unique effects. While LSD uniquely reduced integrity in the default-mode network (DMN), the amphetamines, in contrast to our expectations, reduced integrity in more networks than LSD. However, LSD exhibited more pronounced segregation effects, characterized solely by decreases, in contrast to the amphetamines, which also induced increases. Across all substances, seed-based connectivity mostly increased between networks, with LSD demonstrating more pronounced effects than both amphetamines. Finally, while all substances decreased global connectivity in visual areas, compared to placebo, LSD specifically increased global connectivity in the basal ganglia and thalamus. These findings advance our understanding of the distinctive neurobiological effects of psychedelics, prompting further exploration of their therapeutic potential.

We examined the prospective associations between nicotine dependence and the likelihood of psychiatric and substance use disorders in the general adult population. Participants came from a nationally representative sample of US adults aged 18 years or older, who were interviewed 3 years apart in the National Epidemiologic Survey on Alcohol and Related Conditions (Wave 1, 2001–2002; Wave 2, 2004–2005). The primary analyses were limited to 32,671 respondents (13,751 male (47.9% weighted); mean age of 45 years (SD = 0.18)) who were interviewed in both waves. We used multiple regression and propensity score matching (PSM) to estimate the strength of independent associations between nicotine dependence related to the use of tobacco products at Wave 1 and incident psychiatric disorders at Wave 2. Psychiatric disorders were measured with a structured interview (Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV). All analyses adjusted for multiple potential confounders, including childhood (family history of substance use disorders, parental loss, vulnerable family environment), early-adolescence (self-esteem, social deviance, conduct disorder), late-adolescence (education, personality and psychiatric disorders), adulthood (divorce, stressful life events, social deviance, quality of life, history of alcohol or other substance use disorder), and sociodemographic factors. Multiple regression analysis and PSM converged in indicating that nicotine dependence was associated with significantly increased incidence of any psychiatric disorder (OR = 1.39(95%CI:1.20;1.60)), including substance use disorders (OR = 1.91(95%CI:1.47;2.47)), and anxiety disorders (OR = 1.31(95%CI:1.06;1.62)). Population Attributable Risk Proportions were substantial, ranging from 12.5%(95%CI:8.10;17.0) for any psychiatric disorder to 33.3%(95%CI:18.7;48.0) for any other drug use disorder. Supplementary analyses also indicated significant associations between nicotine dependence and persistence of psychiatric and substance use disorders among patients having a disorder at Wave 1. In the general adult population, nicotine dependence is associated with an increased likelihood for several psychiatric and substance use disorders. Given its high prevalence, these findings have important public health implications.

Depression is a multifactorial clinical syndrome with a low pharmacological treatment response rate. Therefore, identifying predictors of treatment response capable of providing the basis for future developments of individualized therapies is crucial. Here, we applied model-free and model-based measures of whole-brain turbulent dynamics in resting-state functional magnetic resonance imaging (fMRI) in healthy controls and unmedicated depressed patients. After eight weeks of treatment with selective serotonin reuptake inhibitors (SSRIs), patients were classified as responders and non-responders according to the Hamilton Depression Rating Scale 6 (HAMD6). Using the model-free approach, we found that compared to healthy controls and responder patients, non-responder patients presented disruption of the information transmission across spacetime scales. Furthermore, our results revealed that baseline turbulence level is positively correlated with beneficial pharmacological treatment outcomes. Importantly, our model-free approach enabled prediction of which patients would turn out to be non-responders. Finally, our model-based approach provides mechanistic evidence that non-responder patients are less sensitive to stimulation and, consequently, less prone to respond to treatment. Overall, we demonstrated that different levels of turbulent dynamics are suitable for predicting response to SSRIs treatment in depression.

Schizophrenia (SCZ) is a complex mental disorder characterized by a range of symptoms, including positive and negative symptoms, as well as cognitive impairments. Despite the extensive research, the underlying neurobiology of SCZ remain elusive. To overcome this challenge, the use of diverse laboratory modeling techniques, encompassing cellular and animal models, and innovative approaches like induced pluripotent stem cell (iPSC)-derived neuronal cultures or brain organoids and genetically engineered animal models, has been crucial. Immortalized cellular models provide controlled environments for investigating the molecular and neurochemical pathways involved in neuronal function, while iPSCs and brain organoids, derived from patient-specific sources, offer significant advantage in translational research by facilitating direct comparisons of cellular phenotypes between patient-derived neurons and healthy-control neurons. Animal models can recapitulate the different psychopathological aspects that should be modeled, offering valuable insights into the neurobiology of SCZ. In addition, invertebrates' models are genetically tractable and offer a powerful approach to dissect the core genetic underpinnings of SCZ, while vertebrate models, especially mammals, with their more complex nervous systems and behavioral repertoire, provide a closer approximation of the human condition to study SCZ-related traits. This narrative review provides a comprehensive overview of the diverse modeling approaches, critically evaluating their strengths and limitations. By synthesizing knowledge from these models, this review offers a valuable source for researchers, clinicians, and stakeholders alike. Integrating findings across these different models may allow us to build a more holistic picture of SCZ pathophysiology, facilitating the exploration of new research avenues and informed decision-making for interventions.

Currently available clinical treatments on alcohol use disorder (AUD) exhibit limited efficacy and new druggable targets are required. One promising approach to discover new molecular treatment targets involves the transcriptomic profiling of brain regions within the addiction neurocircuitry, utilizing animal models and postmortem brain tissue from deceased patients with AUD. Unfortunately, such studies suffer from large heterogeneity and small sample sizes. To address these limitations, we conducted a cross-species meta-analysis on transcriptome-wide data obtained from brain tissue of patients with AUD and animal models. We integrated 36 cross-species transcriptome-wide RNA-expression datasets with an alcohol-dependent phenotype vs. controls, following the PRISMA guidelines. In total, we meta-analyzed 964 samples – 502 samples from the prefrontal cortex (PFC), 282 nucleus accumbens (NAc) samples, and 180 from amygdala (AMY). The PFC had the highest number of differentially expressed genes (DEGs) across rodents, monkeys, and humans. Commonly dysregulated DEGs suggest conserved cross-species mechanisms for chronic alcohol consumption/AUD comprising MAPKs as well as STAT, IRF7, and TNF. Furthermore, we identified numerous unique gene sets that might contribute individually to these conserved mechanisms and also suggest novel molecular aspects of AUD. Validation of the transcriptomic alterations on the protein level revealed interesting targets for further investigation. Finally, we identified a combination of DEGs that are commonly regulated across different brain tissues as potential biomarkers for AUD. In summary, we provide a compendium of genes that are assessable via a shiny app, and describe signaling pathways, and physiological and cellular processes that are altered in AUD that require future studies for functional validation.

Autism spectrum disorder (ASD) represents a complex of neurological and developmental disabilities characterized by clinical and genetic heterogeneity. While the causes of ASD are still unknown, many ASD risk factors are found to converge on intracellular quality control mechanisms that are essential for cellular homeostasis, including the autophagy-lysosomal degradation pathway. Studies have reported impaired autophagy in ASD human brain and ASD-like synapse pathology and behaviors in mouse models of brain autophagy deficiency, highlighting an essential role for defective autophagy in ASD pathogenesis. To determine whether altered autophagy in the brain may also occur in peripheral cells that might provide useful biomarkers, we assessed activities of autophagy in lympoblasts from ASD and control subjects. We find that lymphoblast autophagy is compromised in a subset of ASD participants due to impaired autophagy induction. Similar changes in autophagy are detected in postmortem human brains from ASD individuals and in brain and peripheral blood mononuclear cells from syndromic ASD mouse models. Remarkably, we find a strong correlation between impaired autophagy and intellectual disability in ASD participants. By depleting the key autophagy gene Atg7 from different brain cells, we provide further evidence that autophagy deficiency causes cognitive impairment in mice. Together, our findings suggest autophagy dysfunction as a convergent mechanism that can be detected in peripheral blood cells from a subset of autistic individuals, and that lymphoblast autophagy may serve as a biomarker to stratify ASD patients for the development of targeted interventions.

Alcohol use disorder (AUD) and binge drinking are highly prevalent public health issues. The stomach-derived peptide ghrelin, and its receptor, the growth hormone secretagogue receptor (GHSR), both of which are expressed in the brain and periphery, are implicated in alcohol-related outcomes. We previously found that systemic and central administration of GHSR antagonists reduced binge-like alcohol drinking, whereas a ghrelin vaccine did not. Thus, we hypothesized that central GHSR drives binge-like alcohol drinking independently of peripheral ghrelin. To investigate this hypothesis, we antagonized β₁-adrenergic receptors (β₁ARs), which are required for peripheral ghrelin release, and combined them with GHSR blockers. We found that both systemic β₁AR antagonism with atenolol (peripherally restricted) and metoprolol (brain permeable) robustly decreased plasma ghrelin levels. Also, ICV administration of atenolol had no effect on peripheral endogenous ghrelin levels. However, only metoprolol, but not atenolol, decreased binge-like alcohol drinking. The β₁AR antagonism also did not prevent the effects of the GHSR blockers JMV2959 and PF-5190457 in decreasing binge-like alcohol drinking. These results suggest that the GHSR rather than peripheral endogenous ghrelin is involved in binge-like alcohol drinking. Thus, GHSRs and β₁ARs represent possible targets for therapeutic intervention for AUD, including the potential combination of drugs that target these two systems.

Psychiatric disorders such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are characterized by altered cognition and mood, brain functions that depend on information processing by cortical microcircuits. We hypothesized that psychiatric disorders would display cell type-specific transcriptional alterations in neuronal subpopulations that make up cortical microcircuits: excitatory pyramidal (PYR) neurons and vasoactive intestinal peptide- (VIP), somatostatin- (SST), and parvalbumin- (PVALB) expressing inhibitory interneurons. Using laser capture microdissection followed by RNA sequencing (LCM-seq), we performed cell type-specific molecular profiling of subgenual anterior cingulate cortex, a region implicated in mood and cognitive control. We sequenced libraries from 130 whole cells pooled per neuronal subtype (VIP, SST, PVALB, superficial and deep PYR) in 76 subjects from the University of Pittsburgh Brain Tissue Donation Program, evenly split between MDD, BD and SCZ subjects and healthy controls (totaling 380 bulk transcriptomes from ~50,000 neurons). We identified hundreds of differentially expressed (DE) genes and biological pathways across disorders and neuronal subtypes, with the vast majority in interneurons, particularly PVALB. While DE genes were unique to each cell type, there was a partial overlap across disorders for genes involved in the formation and maintenance of neuronal circuits. We observed coordinated alterations in biological pathways between select pairs of microcircuit cell types, also partially shared across disorders. Finally, DE genes coincided with known risk variants from psychiatric genome-wide association studies, suggesting cell type-specific convergence between genetic and transcriptomic risk for psychiatric disorders. Our study suggests transdiagnostic cortical microcircuit pathology in SCZ, BD, and MDD and sets the stage for larger-scale studies investigating how cell circuit-based changes contribute to shared psychiatric risk.