Faculty Bibliography

Murine studies show that the gut microbiota-the collection of the microbes residing in the large intestine-affects memory performance in the host. However, whether commensal gut bacteria are linked to human episodic memory remains unknown. Here, we investigated whether individual differences in episodic memory performance were associated with differences in the indigenous gut microbiota composition between individuals. We show that greater gut microbiota α diversity was associated with better item recognition and that gut microbiota dissimilarity index (β diversity) between participants was associated with differences in their performance. Finally, our results suggest that Prevotella copri might play a role in the relationship between gut microbiota and human item recognition in healthy individuals. In a sample size larger than previous human studies and examining unmanipulated gut microbiota, we provide evidence that episodic memory in healthy humans is linked to their gut microbiota composition.

IntroductionBipolar depression is disabling and often inadequately responsive to medication alone. The current efficacy evidence of transcranial magnetic stimulation (TMS) for bipolar depression is conflicting. Therefore, we synthesized randomized controlled trials (RCTs) that tested the efficacy, safety, and tolerability of TMS for bipolar depression.MethodsWe searched MEDLINE/EMBASE/Cochrane/PsycINFO/gray literature (01/10/2025) for RCTs comparing any TMS protocol with sham. Co-primary outcomes were depressive symptoms, all-cause discontinuation; secondary outcomes were response, remission. Risk of bias (RoB) was assessed with RoB-2. Random-effects models estimated standardized mean differences (SMDs) and risk ratios (RRs) with 95% confidence intervals (95%CI), alongside sensitivity, subgroup, and meta-regression analyses.ResultsNineteen comparisons from 17 RCTs (N = 563; TMS = 293, sham = 270; mean N TMS = 15.4, sham = 15.9; mean duration = 2.40 weeks; RoB "low" = 35%, "some concerns" = 65%) were included. Among trials reporting subtypes (k = 13), 41.8% of participants had bipolar I disorder, and 58.2% had bipolar II disorder. The left dorsolateral prefrontal cortex was the most common target (k = 12). TMS reduced depressive symptoms versus sham (SMD = -0.34; 95%CI = -0.58 to -0.11), with no difference in all-cause discontinuation. TMS was favoured for response (RR = 1.41; 95%CI = 1.10 to 1.80) and remission (RR = 1.54; 95%CI = 1.06 to 2.23). However, these effects were not consistently confirmed in sensitivity or subgroup analyses by RoB, TMS type, stimulation site, or treatment resistance. Overall, 15 comparisons (88.2%) did not show superiority of TMS over sham for depressive symptoms at the individual trial level. No seizures or serious adverse events occurred; adverse events did not differ from sham. Meta-regression suggested a greater number of total pulses was associated with greater depressive symptom reduction (β = -0.018; p = .00017).ConclusionsTMS shows a small meta-analytic antidepressant effect and acceptable tolerability in bipolar depression despite most individual trials being negative. However, subgroups and sensitivity findings did not support TMS as an efficacious treatment at current doses. Further testing via larger RCTs with higher-dose protocols is warranted.

[This corrects the article DOI: 10.3389/fpsyt.2025.1623358.].

OBJECTIVE:To estimate associations of more than minimal prenatal nicotine, alcohol, cannabis, and opioid exposures with gestational age, birth weight, and birth weight for gestational age. METHODS:Data were drawn from the HEALthy Brain and Child Development (HBCD) Study, a multisite, longitudinal study in the United States. Predefined recruitment thresholds for each substance were assessed using maternal self-report, maternal toxicology results, and newborn substance exposure-related diagnoses. Birth outcomes included gestational age at delivery (weeks), birth weight (grams), and birth weight for gestational age (centiles). Mean differences and risk ratios for the associations between substance exposure and birth outcomes were estimated using multilevel mixed-effect linear regression or multilevel mixed-effect Poisson regression. RESULTS:Among 660 mother-infant dyads, 17% (n = 115) of participants met recruitment thresholds for prenatal cannabis, 15% for nicotine (n = 102), 13% for alcohol (n = 86), and 5% for opioids (n = 32). In adjusted models, prenatal cannabis and opioid exposures were each associated with lower birth weight (cannabis: -272.2 [95% CI -444.6 to -99.8] g; opioids: -295.4 [95% CI -574.9 to -15.9] g) and birth weight centiles (cannabis: -8.2 [95% CI -15.3 to -1.1] centiles; opioids: -14.4 [95% CI -25.5, -3.4] centiles), although the results were sensitive to model specifications. Prenatal nicotine and alcohol estimates were in similar directions but not statistically significant. No significant associations between exposures and gestational age at delivery were detected. CONCLUSIONS:In this initial HBCD Study data release, more than minimal exposure to cannabis and opioids was associated with smaller birth size, adding evidence to an inconsistent literature. Future studies from HBCD can more deeply interrogate timing and dose of each substance and expand to childhood outcomes.

Higher predicted brain age difference has been associated with several psychiatric disorders. Generalized anxiety disorder (GAD) is associated with markers of accelerated aging. In this study, we determined brain predicted age difference (PAD) in individuals with GAD and healthy controls (HC) as well as group differences in PAD variability using voxel-wise structural MRI. The training dataset included 3511 controls, and the testing dataset included 1595 individuals with GAD and 4552 HC from the ENIGMA-Anxiety GAD Working Group. A convolutional neural network model using four input modalities per subject and a model ensemble approach was used to predict brain age. The PAD was then calculated by subtracting chronological age from the predicted age. Model performance was consistent with other image-based brain age prediction models with similar accuracy across the training set (mean absolute error (MAE) = 2.95 years) and HC in the testing set (MAE = 2.94). We found no evidence of accelerated brain aging in individuals with GAD compared to individuals without GAD, though we did find evidence for greater variation in PAD for individuals with GAD (Levene's test: W = 442.98, p < 0.001) and evidence for greater variability in PAD of those with GAD over 25 years of age. In several exploratory analyses, we found that symptom severity related significantly to PAD, even after controlling for medication and comorbid diagnoses, echoing previous brain age research. These findings underscore the need for consideration of heterogeneity and dimensionality of psychopathology when examining brain age predicted differences.

Childhood is a period of peak developmental plasticity, involving drastic changes in the maturation of the neural circuitry underlying fear learning. Disruption and atypical development of fear learning are candidate mechanisms underlying child psychopathology. While there is a lack of understanding behind the maturation of fear learning systems in humans, rodent studies in this area delineate the normative development of fear learning systems early in life, and the effects of early threatening and fearful experiences on this developmental trajectory. Here, we review the rodent literature on developmental fear learning, as well as human studies that show translational convergence in typical development and children exposed to early life threat. We identify several gaps in research, including the role that caregivers play in regulating fear learning at different developmental stages and the intergenerational transmission of learned fear. Finally, we provide recommendations on how to address these gaps in a way that would improve our developmental frameworks of fear learning.

Executive function (EF), which includes inhibitory control, working memory, and cognitive flexibility, supports adaptive behavior and predicts long-term academic, social, and mental health outcomes. While EF-related neural networks mature throughout childhood, their earliest developmental origins remain unclear. Large-scale brain systems begin organizing in utero, but whether fetal connectivity prospectively relates to EF has not been tested. We collected resting-state fMRI from 113 fetuses (26-39 weeks gestation). Executive function at age 5 was assessed using the Behavior Rating Inventory of Executive Function-Preschool Version (BRIEF-P), resulting in 52 cases with both usable imaging and outcome data after applying motion and birth-outcome criteria. Whole-brain functional connectivity matrices (197 ROIs) were parcellated into 15 networks, and enrichment analysis identified network pairs with a higher-than-expected density of brain-behavior associations. Six enriched network pairs were associated with global EF, including Frontal, Default Mode Network (DMN), Cerebellar, Salience, and Visual networks. Stronger positive connectivity in Frontal-Salience, DMN-Visual, and Cerebellar-DMN predicted poorer EF, whereas greater negative connectivity in Cerebellar-Visual and Salience-Salience predicted better EF. Subscale analyses revealed both shared and distinct associations across EF domains, with Cerebellar and Salience networks consistently implicated. These findings provide the first evidence linking fetal functional architecture to later EF, highlighting distributed, beyond-frontal systems as early scaffolds of executive control.

OBJECTIVE:Phthalates are recognized endocrine disruptors and emerging neurotoxicants. Prenatal exposure to di-2-ethylhexyl phthalate (DEHP) has been linked to adverse neurodevelopmental and neuropsychiatric outcomes, and maternal oxidative stress may play a mechanistic role in prenatal DEHP's neurotoxicity. MATERIALS AND METHODS/METHODS:Participants were drawn from the New York University Children's Health and Environment Study. Prenatal DEHP exposure and maternal lipid peroxidation were assessed using repeated creatinine-adjusted maternal urinary measurements across pregnancy, collected from January 2016-April 2020. Neonatal brain-derived neurotrophic factor (BDNF) was measured in cord serum (N = 337), and internalizing and externalizing problems were assessed at an average age of 2 years using the Child Behavior Checklist for Ages 1.5-5 (CBCL 1½-5) (N = 824). DEHP metabolites (mEHHP; mEOHP; mECPP) were averaged across pregnancy, and cumulative lipid peroxidation biomarkers (8-iso-PGF2α; 15-PGF2α; 8,15-PGF2α; MDA) were estimated using area-under-the-curve values from linear mixed-effects spline models. Partial least squares path modeling evaluated direct and indirect associations using latent constructs for DEHP exposure, lipid peroxidation, CBCL 1½-5, and socioeconomic status; other covariates were modeled as single variables. Sex differences were assessed using bootstrapping and sex-stratified models, adjusting for maternal and child age, parity, pre-pregnancy body mass index, cotinine exposure, and socioeconomic status. RESULTS:Prenatal DEHP exposure was positively associated with maternal lipid peroxidation in all models (β's = 0.11-0.27). Sex-stratified analyses showed that prenatal DEHP exposure was positively associated with CBCL 1½-5 in male children only (β = 0.11), but not with BDNF in either sex. Maternal lipid peroxidation was not associated with BDNF or CBCL 1½-5 in either sex. CONCLUSION/CONCLUSIONS:Prenatal DEHP exposure is associated with maternal oxidative stress and total behavioral problems in male children only, but maternal oxidative stress does not mediate these relationships. Alternative upstream mechanisms may underlie both maternal oxidative stress and neurobehavioral outcomes. Future studies should investigate endocrine, metabolic, and epigenetic pathways to clarify DEHP neurotoxicity.

While attention-deficit/hyperactivity disorder (ADHD) medications, particularly stimulants, are among the most effective treatments in psychiatry, there remains a need for novel alternatives, as not all individuals with ADHD respond to or tolerate currently available medications. We aimed to provide an up-to-date overview of randomised controlled trials (RCTs) of agents either not approved for ADHD or approved for ADHD but tested for off-label indications. We updated, using the same methodology, two previous reviews (Cortese et al, 2023 exploring agents in the pipeline for children with ADHD, and Veronesi et al, 2024, focusing on RCTs of novel compounds in adults with ADHD). For the update, we searched ClinicalTrials.gov and the European Union-based EU Clinical Trials registers up to December 14, 2025. Including the RCTs retrieved by the two previous reviews and those from the updated search, we identified a total of 53 eligible RCTs. Of these, 11 reported results in children and adolescents, and 11 in adults. Considering agents with at least two positive trials for ADHD core symptoms without negative trials, only dasotraline, in children, and centanafadine, in adults, emerged as promising (however, the dasotraline development programme was halted in 2020). This review also includes a discussion of opportunities for advancing the development of novel, effective agents and maximising the benefits of currently available options.

The clinical management of a complex disorder such as schizophrenia remains a significant challenge worldwide. This disorder requires a comprehensive, integrated and personalized care that blends multiple approaches, and the real-world availability of multiple resources. We present here the first recommendations addressing the real-world comprehensive care for people with schizophrenia-spectrum psychoses across different approaches, clinical stages, and levels of available resources. The recommendations are based on a critical review of the scientific literature and a collaborative appraisal by numerous clinical academics actively treating people with schizophrenia worldwide, representing various countries and clinical settings, including those in the Global South. Experts by experience were also involved. Our recommendations indicate that the comprehensive care of schizophrenia should involve: a) early detection; b) measurement-based monitoring; c) pharmacological treatments; d) psychological interventions; e) psychosocial interventions (including supported employment, housing and education); f) management of somatic conditions; g) community care; h) inpatient care; i) peer support, self-help, and alternative healing methods; j) population-level prevention, and l) societal-level support. The overarching core recommendation is to implement evidence-based care that addresses disparities across high- to middle/low-resource settings, emphasizing early intervention (and prevention when possible), culturally-sensitive paradigms that leverage the local existing resources, and task-sharing models that involve non-professional health care workers and, if possible, traditional healers. In the future, we expect that scalable and resource-saving, evidence-based digital solutions will help extend and improve care quality and efficiency across all resource settings. However, none of this can be achieved without adequately focusing on and strengthening mental health funding, improving access to care, addressing social determinants of health, and recognizing that care for people at risk for or living with schizophrenia is uneven and in need of improvement across all settings.