Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

To summarize insights generated during the preceding four conventions of the European Access Academy (EAA) regarding the interface of patient organizations and medical societies with the evolving European Union (EU) health technology assessment (HTA) process.

In 2022 and 2023 four EAA conventions were held on the EU HTA regulation, focusing on: (i) its relevance for beating cancer; (ii) stakeholder involvement; (iii) recommended preparatory steps to ensure its successful implementation; and (iv) the role of hematology and oncology as a pacemaker for the EU HTA process. Here we summarize insights generated at the four EAA conventions about the integration of patient and clinician insights in the evolving EU HTA process, including joint scientific consultations (JSC) and joint clinical assessments (JCA).

Throughout the conventions it became clear that the interface of patient associations and clinical societies with the EU HTA process is key for successful implementation of the regulation. All involved stakeholders rely on the principles of evidence-based medicine (EBM), including best internal and external evidence, patient values and expectations, and clinical experience. It was agreed that patient and clinician perspectives on the assessments are needed to balance the technical analysis of best external evidence. While patient input is rather well defined, when and how input from clinical societies is best incorporated during the process remains unclear.

As stipulated by the EBM triad, systematic involvement of patients and clinicians throughout both JSC and JCA is key to ensuring best outcomes for patients and society as a whole, in line with the objectives of the EU HTA regulation.

Psychiatric disorders are more prevalent in children with mild (MID) to borderline intellectual functioning (BIF). Rare pathogenic variants in neurodevelopmental genes increase the risk for psychiatric disorders and may explain the comorbidity. Despite these patients represent up to 35% of those attended at mental health services, genetic diagnosis is usually not offered. The identification of mentioned variants could lead to improved clinical care.

To identify pathogenic variants responsible of the psychiatric disorders in mild and borderline intellectual functioning.

To correlate phenotypic and genetic profiles to personalize diagnostic, clinical care and support to clinicians and families.

Whole exome sequencing (WES) was performed on 99 enrolled children/adolescent (6-18 yo) affected by a psychiatric condition diagnosed following DSM-5 criteria, and either MID (IQ 55-69) or BIF (IQ 70-85). Severity and interference of IQ and psychiatric comorbidity was evaluated using several psychometric tests (Conners, CDI, STAIC, CAARMS, CBCL and hONOSCA). Inheritance pattern was assessed through Sanger sequencing. ACMG/AMP guidelines were used for variant classification.

In our cohort, 64% patients presented BIF and 36% MID. 45% of the patients had 2 or more psychiatric diagnoses, the most prevalent (87%) being attention deficit hyperactivity disorder and, in second place, autism spectrum disorder (51%).

WES identified pathogenic/likely pathogenic variants in 30% of analyzed patients (30/99), 80% of the variants were de novo. There is no significant difference in patient severity between those with a genetic diagnosis and those without.

Rare deleterious and de novo variants in neurodevelopmental genes are responsible for the comorbidity that exists between psychiatric disorders and mild/borderline intellectual disability.

The high diagnostic yield obtained from our exome sequencing approach demonstrates the need to offer genetic testing in children with psychiatric disorders and comorbid mild to borderline intellectual functioning.

Finally, patients being identified with a genetic diagnosis are subsequently attended in a specialised unit for rare disorders to receive personalised clinical management.

None Declared

People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown.

We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other.

Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone.

CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice.

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Patients with functional neurological disorders (FND) often present with multiple motor, sensory, psychological and cognitive symptoms. In order to explore the relationship between these common symptoms, we performed a detailed clinical assessment of motor, non-motor symptoms, health-related quality of life (HRQoL) and disability in a large cohort of patients with motor FND. To understand the clinical heterogeneity, cluster analysis was used to search for subgroups within the cohort.

One hundred fifty-two patients with a clinically established diagnosis of motor FND were assessed for motor symptom severity using the Simplified Functional Movement Disorder Rating Scale (S-FMDRS), the number of different motor phenotypes (i.e. tremor, dystonia, gait disorder, myoclonus, and weakness), gait severity and postural instability. All patients then evaluated each motor symptom type severity on a Likert scale and completed questionnaires for depression, anxiety, pain, fatigue, cognitive complaints and HRQoL.

Significant correlations were found among the self-reported and all objective motor symptoms severity measures. All self-reported measures including HRQoL correlated strongly with each other. S-FMDRS weakly correlated with HRQoL. Hierarchical cluster analysis supplemented with gap statistics revealed a homogenous patient sample which could not be separated into subgroups.

We interpret the lack of evidence of clusters along with a high degree of correlation between all self-reported and objective measures of motor or non-motor symptoms and HRQoL within current neurobiological models as evidence to support a unified pathophysiology of ‘functional’ symptoms. Our results support the unification of functional and somatic syndromes in classification schemes and for future mechanistic and therapeutic research.

It has not yet been determined if the commonly reported cannabis–psychosis association is limited to individuals with pre-existing genetic risk for psychotic disorders.

We examined whether the relationship between polygenic risk score for schizophrenia (PRS-Sz) and psychotic-like experiences (PLEs), as measured by the Community Assessment of Psychic Experiences-42 (CAPE-42) questionnaire, is mediated or moderated by lifetime cannabis use at 16 years of age in 1740 of the individuals of the European IMAGEN cohort. Secondary analysis examined the relationships between lifetime cannabis use, PRS-Sz and the various sub-scales of the CAPE-42. Sensitivity analyses including covariates, including a PRS for cannabis use, were conducted and results were replicated using data from 1223 individuals in the Dutch Utrecht cannabis cohort.

PRS-Sz significantly predicted cannabis use (p = 0.027) and PLE (p = 0.004) in the IMAGEN cohort. In the full model, considering PRS-Sz and covariates, cannabis use was also significantly associated with PLE in IMAGEN (p = 0.007). Results remained consistent in the Utrecht cohort and through sensitivity analyses. Nevertheless, there was no evidence of a mediation or moderation effects.

These results suggest that cannabis use remains a risk factor for PLEs, over and above genetic vulnerability for schizophrenia. This research does not support the notion that the cannabis–psychosis link is limited to individuals who are genetically predisposed to psychosis and suggests a need for research focusing on cannabis-related processes in psychosis that cannot be explained by genetic vulnerability.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Depressed patients with early traumatic experiences may represent a clinically distinct subtype with worse clinical outcome. Since early traumatic experiences alter the development of systems that regulate the stress response, certain personality features may influence coping strategies, putting individuals with depression and a history of early traumatic experiences at greater risk of suicidal behaviour.

To determine whether impulsivity mediates the relationship between early traumatic experiences and suicidal behaviour in patients with major depressive disorder (MDD).

The sample included 190 patients [mean age (SD)=53.71 (10.37); females: 66.3%], with current MDD. The Childhood Trauma Questionnaire-Short Form (CTQ-SF), the List of Threatening Experiences (LTE), and the Barratt Impulsiveness Scale-11 (BIS-11) were used to assess childhood and adulthood adverse life events and impulsivity. We developed mediation models by bootstrap sampling methods.

81 (42.6%) patients had previous suicide attempts (SA). CTQ-SF-Total and BIS-11-Total scores were higher in MDD patients with previous SA. Correlation analyses revealed significant correlations between the CTQ-SF-Total and BIS-11-Total, CTQ-SF-Total and HDRS-Total, and BIS-11-Total and HDRS-Total scores. Regression models found that CTQ-SF-Total, BIS-11-Total, and HDRS-Total scores were associated with SA. Mediation analyses further revealed the association between CTQ-SF-Total and SA was mediated by the indirect effect of the BIS-11-Total score (b=0.007, 95% CI=0.001, 0.015), after controlling for sex, HDRS-Total, and LTE-Total.

Impulsivity could mediate the influence of childhood trauma on suicidal behaviour. This will help understand the role of risk factors in suicidal behaviour and aid in the development of prevention interventions focused on modifiable mediators when risk factors are non-modifiable.

Suicidal behavior has a great impact on world public health. The literature describes the possible existence of an association between neurobiological, clinical and cognitive factors in suicidal behavior.

To determine the possible relationship between clinical variables (history of abuse/maltreatment in childhood), psychopathology (impulsivity traits) and cognitive (decision-making) with a history of suicide attempt and/or current suicidal idea in patients with major depressive disorder.

Cross-sectional study in a sample of adult patients with major depressive disorder in which two types of comparisons are made. In the first case, two groups were compared based on the presence or absence of history of suicide attempt. In the second case, two groups were compared based on the presence or absence of suicidal ideation in the same sample of patients. Finally, sociodemographic, clinical and cognitive variables were evaluated in that population sample.

When the joint influence of sociodemographic, clinical and cognitive characteristics are present, it can be said that being single/divorced/separated, a history of sexual abuse in childhood and an alteration in decision-making, specifically a lower number of choices of deck D in the IGT test, are associated with a higher probability of a personal history of suicide attempt. While a higher score on the Barrat impulsivity scale is associated with a greater probability of presenting current suicidal ideation once the influence of sociodemographic, clinical and cognitive variables has been taken into account.

Different sociodemographic, clinical and cognitive factors are associated with the presence of a history of suicide attempt and/or current suicidal ideation.

No significant relationships.