Faculty Bibliography

BACKGROUND/OBJECTIVES/OBJECTIVE:Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive malignancies with a challenging prognosis, especially for patients with Neurofibromatosis type 1 (NF1). Their low incidence necessitates comprehensive studies to investigate the survival outcome. METHODS:We conducted a systematic review and meta-analysis, including data from 16 studies and 4265 patients, to explore surgical outcomes and survival rates, focusing on time-related outcomes, including overall survival (OS), progression-free survival (PFS), and recurrence rate. RESULTS:The analysis revealed that the OS rate was 86% [95% CI: 75-97%] at 1 year, decreasing to 60% [95% CI: 45-75%] at 3 years, and further declining to 47% [95% CI: 35-58%] by 5 years. For PFS, the 1-year rate was 61% [95% CI: 25-98%], which remained similar at 62% [95% CI: 35-89%] for 3 and 5 years. In NF1-associated MPNSTs, the 1-year OS was relatively high at 93% [95% CI: 83-100%], but it dropped to 68% [95% CI: 53-84%] at 3 years and further to 50% [95% CI: 31-68%] at 5 years. Additionally, the hazard ratio indicated a 38% lower survival rate in NF1 patients than those with sporadic MPNSTs when data were presented in the same study. Recurrence rates were high, with 56% of patients experiencing a relapse, primarily as local recurrences (70.6%). Mortality was significant, with over 50% of patients dying within an average follow-up period of 33.45 months. CONCLUSIONS:MPNSTs, particularly in NF1 patients, are associated with poor prognosis and high recurrence rates. These results underline the necessity of targeted therapeutic strategies and improved programs for screening, mainly through a multidisciplinary approach to optimize management.

BACKGROUND:Maternal infections are linked to neurodevelopmental impairments, highlighting the need to investigate SARS-CoV-2-induced immune activation. OBJECTIVE:This study aimed to evaluate the impact of maternal infection on neurodevelopment and investigate whether cytokine and chemokine profiles predict delays at 24 months. METHODS:Conducted in Brazil (January 2021-March 2022), this follow-up study included 18 SARS-CoV-2 positive pregnant women at 35-37 weeks' gestation, 15 umbilical cord blood samples, and blood samples from 15 children at 6 months and 14 at 24 months. Developmental delay was defined using the Bayley Scales of Infant and Toddler Development, Third Edition, with scores below 90 in cognitive, communication, or motor domains. RESULTS:At 6 months, 33.3% of infants exhibited cognitive delays, 20% communication delays, and 40% motor delays, increasing to 35.71%, 64.29%, and 57.14% at 24 months, respectively. Elevated interferon-gamma and tumor necrosis factor-alpha in cord blood correlated with cognitive delays, while interleukin (IL)-6, IL-8, IL-17, and IL-1β were associated with motor delays. Increased C-X-C motif chemokine ligand 10 and other cytokines were associated with communication delays. CONCLUSION/CONCLUSIONS:Maternal SARS-CoV-2 may impact infant neurodevelopment, as early cytokine elevations correlate with delays, highlighting the importance of early monitoring and interventions to reduce long-term effects. IMPACT/CONCLUSIONS:Prenatal SARS-COV-2 infection in pregnant women is linked to developmental delays in toddlers, with cytokine and chemokine changes associated with neurodevelopmental outcomes at 24 months. This study shows the long-term impact of maternal SARS-COV-2 infection on child development, highlighting inflammatory markers like IFN-γ, TNFα, IL-6, IL-8, IL-17, IL-1β, and CXCL10. Identifying specific cytokines correlating with cognitive, communication, and motor delays suggests potential biomarkers for early intervention. Conducted in Fortaleza, Brazil, the study emphasizes understanding local epidemiological impacts on child development, especially in regions with high infection rates. Graphical depiction of the SARS-CoV-2-induced maternal immune activation and its impact on the child's neurological development. Maternal immune activation from SARS-CoV-2 infection can affect a baby's neurological development, leading to motor, communication, and cognitive delays, assessed at 6 and 24 months old. Alterations in cytokine and chemokine levels in cord blood at six months may help predict these adverse outcomes observed at 24 months.

Sleep disturbances are prominent across neurodevelopmental disorders (NDDs) and may reflect specific abnormalities in brain development and function. Overnight polysomnography (PSG) allows for detailed investigation of sleep architecture, offering a unique window into neurocircuit function. Analysis of existing pediatric PSGs from clinical studies could enhance the availability of sleep studies in pediatric patients with NDDs towards a better understanding of mechanisms underlying abnormal development in NDDs. Here, we introduce and characterize a retrospective collection of 1527 clinical pediatric overnight PSGs across five different sites. We first developed an automated stager trained on independent pediatric sleep data, which yielded better performance compared to a generic stager trained primarily on adults. Using consistent staging across cohorts, we derived a panel of EEG micro-architectural features. This unbiased approach replicated broad trajectories previously described in typically developing sleep architecture. Further, we found sleep architecture disruptions in children with Down's Syndrome (DS) that were consistent across independent cohorts. Finally, we built and evaluated a model to predict age from sleep EEG metrics, which recapitulated our previous findings of younger predicted brain age in children with DS. Altogether, by creating a resource pooled from existing clinical data we expanded the available datasets and computational resources to study sleep in pediatric populations, specifically towards a better understanding of sleep in NDDs. This Retrospective Analysis of Sleep in Pediatric (RASP) cohorts dataset, including staging annotation derived from our automated stager, is deposited at https://sleepdata.org/datasets/rasp.

The objective of this study was to explore the buffering effect of support on the association between stress and postpartum depression (PPD) among immigrant women. We surveyed 223 Chinese pregnant or postpartum (within one year post-delivery) immigrant women in New York City. Surveys were conducted in English, Simplified Chinese or Mandarin, March-June 2021. PPD was measured with the Edinburgh PPD scale (EPDS); scores of 13 or higher indicate probable depression. Perceived stress was measured with one question, "How often did you feel stressed in the past week?"; responses were collapsed into a binary measure: Never/Rarely and Sometimes/Often/Always. Support was assessed with a general question about perception of receiving needed support and the Patient-Reported Outcomes Measurement Information System (PROMIS) V2.0 Short Form Informational, Instrumental, and Emotional Support measures. Bivariate and multivariable general linear regression models assessed the relationship among stress, support, and PPD. The EPDS mean score was 11.9 (95%CI:11.1-12.7) and 50% (95%CI: 42-57%) had EPDS scores ≥ 13, indicative of serious symptoms; 56% felt stressed in the past week and 37% reported getting needed support. Among women without perceived needed support, mean EPDS scores were higher among women who were stressed compared with women who were not (adjusted mean difference (aMD) 5.4; 95%CI:3.3-7.5); the association between stress and EPDS score was attenuated among women with needed support (aMD 1.1; 95%CI:-1.0, 3.1). Similar patterns held for emotional and instrumental support. Perceived and social support attenuated the association between perceived stress and depression symptoms among Chinese immigrant women. Enhancing support may be effective in countering the impact of stressors on PPD.

Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.

This umbrella review synthesizes data on the prevalence of mental disorder symptoms among university students worldwide. A systematic search of seven databases (inception-July 23, 2023) followed PRISMA guidelines. We included meta-analyses assessing the prevalence of mental disorder symptoms, evaluating methodological quality with AMSTAR-2. A random-effects meta-analysis was conducted, along with meta-regression and subgroup analyses for moderators (percentage of females, publication date, healthcare-related degrees, COVID-19 pandemic). We included 1,655 primary studies from 62 meta-analyses, encompassing 8,706,185 participants. AMSTAR-2 ratings classified 35 % of meta-analyses as low quality and 65 % as critically low. Pooled prevalence estimates were: depression-mild (35.41 %, CI=33.9-36.93) and severe (13.42 %, CI=8.03-19.92; k=952; n=2,108,813); anxiety-mild (40.21 %, CI=37.39-43.07) and severe (16.79 %, CI=7.21-29.29; k=433; n=1,579,780); sleep disorders (41.09 %, CI=35.7-46.58); eating disorders (17.94 %, CI=15.79-20.20); gambling disorder (6.59 %, CI=5.52-7.75); post-traumatic stress disorder (25.13 %, CI=20.55-30.02); stress (36.34 %, CI=29.36-43.62); and suicide-related outcomes (ideation past 12 months: 10.76 %, CI=9.53-12.06; lifetime ideation: 20.33 %, CI=16.15-24.86; suicide attempt past 12 months: 1.37 %, CI=0.67-2.29; lifetime attempt: 3.44 %, CI=2.48-4.54). Meta-regression analyses identified statistically significant moderators of prevalence such as healthcare academic degrees and the pandemic in the case of depression and studies with more females in the case of sleep disorders. This is the most comprehensive synthesis on the prevalence of mental disorder symptoms in university students, providing crucial insights for clinicians, policymakers, and stakeholders.

The subgenual anterior cingulate cortex (sgACC) plays a central role in the pathophysiology of major depressive disorder (MDD). Its functional interactive profile with the left dorsal lateral prefrontal cortex (DLPFC) is associated with transcranial magnetic stimulation (TMS) treatment outcomes. Previous research on sgACC functional connectivity (FC) in MDD has yielded inconsistent results, partly due to small sample sizes and limited statistical power. Furthermore, calculating sgACC-FC to target TMS individually is challenging. We used a large multi-site cross-sectional sample (1660 patients with MDD vs. 1341 healthy controls) from Phase II of the Depression Imaging REsearch ConsorTium (DIRECT) to systematically delineate case-control difference maps of sgACC-FC. We explored the potential impact of group-level abnormality profiles on TMS target localization and clinical efficacy. Next, we developed an MDD big data-guided, individualized TMS targeting algorithm to integrate group-level statistical maps with individual-level brain activity to individually localize TMS targets. We found enhanced sgACC-DLPFC FC in patients with MDD compared with healthy controls (HC). These group differences altered the position of the sgACC anti-correlation peak in the left DLPFC. We showed that the magnitude of case-control differences in the sgACC-FC was related to clinical improvement in two independent clinical samples. This targeting algorithm may generate targets demonstrating stronger associations with clinical efficiency than group-level targets. We reliably delineated MDD-related abnormalities of sgACC-FC profiles in a large, independently ascertained sample and demonstrated the potential impact of such case-control differences on FC-guided localization of TMS targets.

BACKGROUND:) that underlies the vulnerability to both physical and mental conditions could have important implications for our approach to health assessment and treatment. OBJECTIVE:in children and adolescents. METHODS:This Swedish registry-based cross-sectional study included children and adolescents born between 1996 and 2003 with follow-up until 2013. We extracted data on 25 mental and physical health conditions according to the ICD-10 system. To determine the optimal dimensional structure of these conditions, several competing measurement models were tested, including correlated factors, one factor, various bifactor specifications and bifactor exploratory structural equation modelling (ESEM). FINDINGS/RESULTS:=0.423; ECV=0.130) factors also indicated additional significant unique contributions. CONCLUSIONS:underlying both mental and physical conditions, alongside distinct domain-specific factors. These findings have important implications for clinical practice, providing evidence that suggests the need for more integrated approaches to health assessment and treatment that consider the interconnectedness of mental and physical health.