The Hierarchical Taxonomy of Psychopathology (HiTOP) and Research Domain Criteria (RDoC) frameworks emphasize transdiagnostic and mechanistic aspects of psychopathology. We used a multi-omics approach to examine how HiTOP’s psychopathology spectra (externalizing [EXT], internalizing [INT], and shared EXT + INT) map onto RDoC’s units of analysis.

We conducted analyses across five RDoC units of analysis: genes, molecules, cells, circuits, and physiology. Using genome-wide association studies from the companion Part I article, we identified genes and tissue-specific expression patterns. We used drug repurposing analyses that integrate gene annotations to identify potential therapeutic targets and single-cell RNA sequencing data to implicate brain cell types. We then used magnetic resonance imaging data to examine brain regions and circuits associated with psychopathology. Finally, we tested causal relationships between each spectrum and physical health conditions.

Using five gene identification methods, EXT was associated with 1,759 genes, INT with 454 genes, and EXT + INT with 1,138 genes. Drug repurposing analyses identified potential therapeutic targets, including those that affect dopamine and serotonin pathways. Expression of EXT genes was enriched in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT + INT liability was associated with reduced gray matter volume in the amygdala and subcallosal cortex. INT genetic liability showed stronger causal effects on physical health – including chronic pain and cardiovascular diseases – than EXT.

Our findings revealed shared and distinct pathways underlying psychopathology. Integrating genomic insights with the RDoC and HiTOP frameworks advanced our understanding of mechanisms that underlie EXT and INT psychopathology.

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in individuals genetically similar to European reference panels (EUR-like; n = 16,400 to 1,074,629). Traits included clinical (e.g. major depressive disorder, alcohol use disorder) and subclinical measures (e.g. risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

Genetic and environmental factors, including adverse childhood experiences (ACEs), contribute to substance use disorders (SUDs). However, the interactions between these factors are poorly understood.

We examined associations between SUD polygenic scores (PGSs), ACEs, and the initiation of use and severity of alcohol (AUD), opioid use disorder (OUD), and cannabis use disorder (CanUD) in 10,275 individuals (43.5% female, 47.2% African-like ancestry [AFR], and 52.8% European-like ancestry [EUR]). ACEs and SUD severity were modeled as latent factors. We conducted logistic and linear regressions within ancestry groups to examine the associations of ACEs, PGS, and their interaction with substance use initiation and SUD severity.

All three SUD PGS were associated with ACEs in EUR individuals, indicating a gene–environment correlation. Among EUR individuals, only the CanUD PGS was associated with initiating use, whereas ACEs were associated with initiating use of all three substances in both ancestry groups. Additionally, a negative gene-by-environment interaction was identified for opioid initiation in EUR individuals. ACEs were associated with all three SUD severity latent factors in EUR individuals and with AUD and CanUD severity in AFR individuals. PGS were associated with AUD severity in both ancestry groups and with CanUD severity in AFR individuals. Gene-by-environment interactions were identified for AUD and CanUD severity among EUR individuals.

Findings highlight the roles of ACEs and polygenic risk in substance use initiation and SUD severity. Gene-by-environment interactions implicate ACEs as moderators of genetic susceptibility, reinforcing the importance of considering both genetic and environmental influences on SUD risk.

Following a wave of terrorist bombings in the mid-1990s, France established Medical-Psychological Emergency Units (MPEUs - “Cellule d’Urgence Médico-Psychologique - CUMP”). These units aim to provide immediate mental health and psychosocial support to victims and emergency responders. During the COVID-19 pandemic, the Bordeaux MPEU pioneered the use of cloud computing to coordinate real-time activity across thirteen regional mental health units that serve 6 million people.

Based on 30 years of disaster psychiatry expertise and national guidelines, this innovative approach was recognized by the governmental Regional Health Agency, leading to the development of an information system application (ISA) specifically tailored for managing mental health and psychosocial support during crisis events.

The alpha version of the ISA for MPEU is being tested locally during the Paris 2024 Olympics. It is a multi-media app that offers various functionalities according to user profile. Volunteers are mobilized via the app on their smartphone, have real-time event tracking, and can record their clinical activity. For unit managers, it facilitates triggering the network, deploying resources, and coordinating real-time responses to the evolving crisis. For institutions, it enables monitoring of the ongoing crisis and adjusting responses. The app, designed for major multi-site events, will be beta tested in a full-scale disaster simulation in Bordeaux.

Data will be collected and reported In October, 2024

The ISA-MPEU improves the network’s capacity to provide rapid and effective support in emergencies, while at the same time providing a research tool through its database of mental health responses.

Malondialdehyde (MDA) is a product of polyunsaturated fatty acid peroxidation (Del Rio D, et al. A review of recent studies on MDA as toxic molecule and biological marker of oxidative stress. Nutr Metab Cardiovasc Dis. 2005;15:316-28). It is a biomarker of oxidative stress and is involved in the pathophysiology of schizophrenia (Goh et al. Asian J Psychiatr. 2022;67:102932). Schizofrenia is linked to disrupted oxidative balance and inflammation (Więdłocha et al. Brain Sci. 2023;13:490). Prior research has shown connections between biomarkers and circadian rhythms in schizophrenia (Morera & Abreu. Acta Physiol Scand. 2007;43:313-14) and diabetes type 2 (Kanabrocki EL, et al. Circadian variation in oxidative stress biomarkers in healthy and type II diabetic men. Chronobiol Int. 2002;19:423-39). To determinate if MDA levels have a role in schizophrenia and follow a circadian rhythm may be useful.

The aim of our study is to compare diurnal and nocturnal MDA serum levels in patients in acute and stabilized phases of schizophrenia according to CIE-10 to find out if there are variations related with circadian rhythms

47 patients were included in our study in two clinical phases: acute episode and stabilization. Blood samples were collected at 12:00h and at 00:00h. MDA serum levels were measured twice: when patients were decompensated (admission) and at clinical stabilization (discharge). The relationship between quantitative variables at both times was analysed by T-Student test

There is no significative difference between night and day MDA levels in the acute phase of the schizophrenia (2.22±1.352 vs. 1.93±1.530, p<0.09). There is statistical significance between 12:00 and 00:00 (1.90±1.136 vs. 1.34±0.868, p<0.001) at discharge: it was observed that levels decreased. This result can be interpreted as there is circadian rhythm in stabilized phases.

MDA levels in patients with schizophrenia do not follow a circadian rhythm in the acute episode. When they are clinically stabilized present a circadian change. These patients lose the circadian rhythm in acute episodes. MDA circadian rhythm may help diagnose the clinical phase and its severity. It is necessary to perform more studies to know its utility as an oxidative biomarker

None Declared

Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.

The aim of this study was to generate an experts’ consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs.

An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health.

Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general.

The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk.

Elucidation of the interaction of biological and psychosocial/environmental factors on opioid dependence (OD) risk can inform our understanding of the etiology of OD. We examined the role of psychosocial/environmental factors in moderating polygenic risk for opioid use disorder (OUD).

Data from 1958 European ancestry adults who participated in the Yale-Penn 3 study were analyzed. Polygenic risk scores (PRS) were based on a large-scale multi-trait analysis of genome-wide association studies (MTAG) of OUD.

A total of 420 (21.1%) individuals had a lifetime diagnosis of OD. OUD PRS were positively associated with OD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.21–1.66). Household income and education were the strongest correlates of OD. Among individuals with higher OUD PRS, those with higher education level had lower odds of OD (OR 0.92, 95% CI 0.85–0.98); and those with posttraumatic stress disorder (PTSD) were more likely to have OD relative to those without PTSD (OR 1.56, 95% CI 1.04–2.35).

Results suggest an interplay between genetics and psychosocial environment in contributing to OD risk. While PRS alone do not yet have useful clinical predictive utility, psychosocial factors may help enhance prediction. These findings could inform more targeted clinical and policy interventions to help address this public health crisis.

To investigate the latent factor structure and construct validity of the Verbal Series Attention Test (VSAT) across clinical patient populations.

Participants included a consecutive series of clinical patients presenting with a primary memory complaint. Each patient underwent a comprehensive neuropsychological assessment and provided informed consent to allow their clinical data to be used for research. Groups formed included 1) No Neurocognitive Disorder [NoND, N=262, mean age=68.8, mean education=16.2, mean MMSE=28.3], 2) Mild Neurocognitive Disorder [MildND, N=337, mean age=72.3, mean education=15.4, mean MMSE=28.7], and 3)

Major Neurocognitive Disorder [MajorND, N=524, mean age=76.5, mean education=14.5, mean MMSE=19.0] with etiologies including suspected Alzheimer’s disease and/or vascular pathology. Latent factors were investigated using exploratory factor analysis (EFA).

EFA was conducted using SAS 9.4 software and the promax (oblique) rotation to reveal the latent factors of the eight timed items of the VSAT in each of the three clinical groups. The structure was essentially identical in all three groups with two primary factors consistently emerging identified as 1-Complex Attention and 2-Simple Attention. Each factor had four items loading with a correlation range of > 0.37 x < 0.92. The internal consistency (Cronbach’s alpha) for the VSAT total score in each group was excellent (NoND a=0.83, MildND a=0.81, and MajorND a=0.84). To investigate construct validity, the VSAT items were entered into factor analysis with measures of attention and executive function (i.e., Digit Span [forward, backward, sequence], Trail Making Test A & B, semantic fluency (animals), Controlled Oral Word Association Test [COWAT, FAS]). All three patient groups were combined (N=950) given the VSAT’s consistent factor structure. Using the same EFA procedure as before, two main factors emerged with the VSAT Complex Attention variables loading on a general complex attention/working memory factor including Trails B, semantic fluency, and Digit Span subtests. The VSAT Simple Attention items loaded on a general attention factor with the VSAT Simple Attention variables and Trails A. COWAT did not load significantly on either factor.

The latent factor structure of the VSAT was consistent across patient populations with excellent internal consistency in each clinical group. The Complex and Simple Attention factors of the VSAT loaded on factors with similar variables identifying the anticipated latent factor structure demonstrating the construct validity of the VSAT across a wide spectrum of cognitive impairment in patients with primary memory complaints ranging from NoND to MajorND. This supports the use of the VSAT in patients across neurocognitive severity. Future studies will further explore additional psychometric properties of this instrument.

Poor mood and quality of life is common among patients with medically intractable seizures. Many of these patients are not candidates for seizure focus resection and continue to receive standard medical care. Responsive neurostimulation (RNS) has been an effective approach to reduce seizure frequency for nonsurgical candidates. Previous research using RNS clinical trial participants has demonstrated improved mood and quality of life when patients received RNS-implantation earlier in their medically resistant epilepsy work-up (Loring et al., 2021). We aimed to describe the level of depression and quality of life in adults with medical resistant epilepsy, treated with RNS, presenting to an outpatient clinic.

This pilot study was conducted among 11 adult epilepsy patients treated with RNS at the epilepsy specialty clinic at Baylor College of Medicine. Ages of participants ranged from 18-56 (M=32.01, SD=12.37) with a mean education of 12.43 (SD=0.85). The majority of the participants identified as White (White=72.2%; Hispanic/Latino/a=14.3%, Other=7.1%). We also present pre- and post-RNS preliminary results of a subset of 4 patients for whom pre and post implantation data was available. Depression symptoms were assessed through the Beck Depression Inventory, 2nd Edition (BDI-II) and quality of life was determined using the Quality of Life in Epilepsy (QoLiE-31).

Patients reported minimal symptoms of depression (M=5.45, SD=4.03) and good overall quality of life (M=71.18, SD=14.83) after RNS. Participants’ scores on their overall quality of life ranged from 50 to 95 (100=better quality of life). The QoLiE-31 showed high scores on emotional wellbeing (M=69.45, SD=14.56) and cognitive functioning (M=65.36, SD=16.66) domains. Post-hoc analysis revealed a significant difference in the cognitive functioning domain of QoLiE-31 before (M=44.75, SD=12.58) and after (M=51.0, SD=11.58) RNS implantation(t(3)=-3.78, p=0.016. Additionally, overall QoLiE score approached statistical significance when comparing pre-RNS (M=44.75 SD=9.29) to post-RNS (M=49.75 SD=11.62; t(3)=-2.01, p = 0.069). No significant differences were evident on seizure worry, energy/fatigue, medication effects, and social functioning domains of QoLiE-31 before and after RNS treatment.

These pilot study results suggest low levels of depression with this population post-RNS implantation. Additionally, there is preliminary evidence to suggest improved patient-rated cognitive functioning and overall quality of life. While this is a small study population, the results have important implications for patients with intractable epilepsy, even with those form who surgical resection may not be possible. Future studies with large enough samples to examine moderating and mediating factors to mood and quality of life changes post-RNS will be important.